config['Classification']['fastr'] = 'True'
config['Classification']['fastr_plugin'] = self.fastr_plugin
config['Classification']['classifiers'] =\
- 'SVM, SVM, SVM, SVM, SVM, SVM, SVM, SVM, SVM, ' +\
- 'RF, RF, RF, ' +\
- 'LR, LR, LR, ' +\
- 'LDA, LDA, LDA, ' +\
- 'QDA, QDA, QDA, ' +\
- 'GaussianNB, GaussianNB, GaussianNB, ' +\
+ 'SVM, RF, LR, LDA, QDA, GaussianNB, ' +\
'AdaBoostClassifier, ' +\
'XGBClassifier'
config['Classification']['max_iter'] = '100000'
@@ -637,7 +632,7 @@ Source code for WORC.WORC
# Hyperparameter optimization options
config['HyperOptimization'] = dict()
config['HyperOptimization']['scoring_method'] = 'f1_weighted'
- config['HyperOptimization']['test_size'] = '0.15'
+ config['HyperOptimization']['test_size'] = '0.2'
config['HyperOptimization']['n_splits'] = '5'
config['HyperOptimization']['N_iterations'] = '1000'
config['HyperOptimization']['n_jobspercore'] = '500' # only relevant when using fastr in classification
@@ -1147,6 +1142,7 @@ Source code for WORC.WORC
self.links_C1_test[label] = self.classify.inputs['features_test'][str(label)] << self.sources_features_test[label].output
self.links_C1_test[label].collapse = 'test'
+
else:
raise WORCexceptions.WORCIOError("Please provide labels.")
else:
@@ -1934,7 +1930,7 @@ Source code for WORC.WORC
self.network.execute(self.source_data, self.sink_data, execution_plugin=self.fastr_plugin, tmpdir=self.fastr_tmpdir)
-[docs] def add_evaluation(self, label_type, modus='classification'):
+[docs] def add_evaluation(self, label_type, modus='binary_classification'):
"""Add branch for evaluation of performance to network.
Note: should be done after build, before set:
diff --git a/WORC/doc/_build/html/_modules/WORC/addexceptions.html b/WORC/doc/_build/html/_modules/WORC/addexceptions.html
index 8724bda4..6ea3064d 100644
--- a/WORC/doc/_build/html/_modules/WORC/addexceptions.html
+++ b/WORC/doc/_build/html/_modules/WORC/addexceptions.html
@@ -8,7 +8,7 @@
- WORC.addexceptions — WORC 3.4.2 documentation
+ WORC.addexceptions — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/classification/AdvancedSampler.html b/WORC/doc/_build/html/_modules/WORC/classification/AdvancedSampler.html
index bb0b2570..7408c95f 100644
--- a/WORC/doc/_build/html/_modules/WORC/classification/AdvancedSampler.html
+++ b/WORC/doc/_build/html/_modules/WORC/classification/AdvancedSampler.html
@@ -8,7 +8,7 @@
- WORC.classification.AdvancedSampler — WORC 3.4.2 documentation
+ WORC.classification.AdvancedSampler — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/classification/ObjectSampler.html b/WORC/doc/_build/html/_modules/WORC/classification/ObjectSampler.html
index 70ee7457..fb08b036 100644
--- a/WORC/doc/_build/html/_modules/WORC/classification/ObjectSampler.html
+++ b/WORC/doc/_build/html/_modules/WORC/classification/ObjectSampler.html
@@ -8,7 +8,7 @@
- WORC.classification.ObjectSampler — WORC 3.4.2 documentation
+ WORC.classification.ObjectSampler — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/classification/RankedSVM.html b/WORC/doc/_build/html/_modules/WORC/classification/RankedSVM.html
index e65a8523..e9a7dae8 100644
--- a/WORC/doc/_build/html/_modules/WORC/classification/RankedSVM.html
+++ b/WORC/doc/_build/html/_modules/WORC/classification/RankedSVM.html
@@ -8,7 +8,7 @@
- WORC.classification.RankedSVM — WORC 3.4.2 documentation
+ WORC.classification.RankedSVM — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/classification/SearchCV.html b/WORC/doc/_build/html/_modules/WORC/classification/SearchCV.html
index c080ac63..9fcd0385 100644
--- a/WORC/doc/_build/html/_modules/WORC/classification/SearchCV.html
+++ b/WORC/doc/_build/html/_modules/WORC/classification/SearchCV.html
@@ -8,7 +8,7 @@
- WORC.classification.SearchCV — WORC 3.4.2 documentation
+ WORC.classification.SearchCV — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/classification/construct_classifier.html b/WORC/doc/_build/html/_modules/WORC/classification/construct_classifier.html
index a91f836c..a6642d40 100644
--- a/WORC/doc/_build/html/_modules/WORC/classification/construct_classifier.html
+++ b/WORC/doc/_build/html/_modules/WORC/classification/construct_classifier.html
@@ -8,7 +8,7 @@
- WORC.classification.construct_classifier — WORC 3.4.2 documentation
+ WORC.classification.construct_classifier — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/classification/createfixedsplits.html b/WORC/doc/_build/html/_modules/WORC/classification/createfixedsplits.html
index de4e1ff2..9d111ccd 100644
--- a/WORC/doc/_build/html/_modules/WORC/classification/createfixedsplits.html
+++ b/WORC/doc/_build/html/_modules/WORC/classification/createfixedsplits.html
@@ -8,7 +8,7 @@
- WORC.classification.createfixedsplits — WORC 3.4.2 documentation
+ WORC.classification.createfixedsplits — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/classification/crossval.html b/WORC/doc/_build/html/_modules/WORC/classification/crossval.html
index 0c547ace..2b0a9074 100644
--- a/WORC/doc/_build/html/_modules/WORC/classification/crossval.html
+++ b/WORC/doc/_build/html/_modules/WORC/classification/crossval.html
@@ -8,7 +8,7 @@
- WORC.classification.crossval — WORC 3.4.2 documentation
+ WORC.classification.crossval — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
@@ -269,6 +269,7 @@ Source code for WORC.classification.crossval
for n_patient in range(0, classes.shape[1]):
for n_label in range(0, classes.shape[0]):
classes_temp[n_patient, n_label] = classes[n_label, n_patient]
+
else:
raise ae.WORCKeyError('{} is not a valid modus!').format(modus)
diff --git a/WORC/doc/_build/html/_modules/WORC/classification/estimators.html b/WORC/doc/_build/html/_modules/WORC/classification/estimators.html
index ff0758df..69f1d45a 100644
--- a/WORC/doc/_build/html/_modules/WORC/classification/estimators.html
+++ b/WORC/doc/_build/html/_modules/WORC/classification/estimators.html
@@ -8,7 +8,7 @@
- WORC.classification.estimators — WORC 3.4.2 documentation
+ WORC.classification.estimators — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/classification/fitandscore.html b/WORC/doc/_build/html/_modules/WORC/classification/fitandscore.html
index 4a58ef1f..f4d639c4 100644
--- a/WORC/doc/_build/html/_modules/WORC/classification/fitandscore.html
+++ b/WORC/doc/_build/html/_modules/WORC/classification/fitandscore.html
@@ -8,7 +8,7 @@
- WORC.classification.fitandscore — WORC 3.4.2 documentation
+ WORC.classification.fitandscore — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
@@ -597,6 +597,7 @@ Source code for WORC.classification.fitandscore
<
X_test = scaler.transform(X_test)
del para_estimator['FeatureScaling']
+ del para_estimator['FeatureScaling_skip_features']
# Delete the object if we do not need to return it
if not return_all:
@@ -719,6 +720,11 @@ Source code for WORC.classification.fitandscore
<
else:
raise ae.WORCKeyError(f'Model {model} is not known for SelectFromModel. Use Lasso, LR, or RF.')
+ if len(y_train.shape) >= 2:
+ # Multilabel or regression. Regression: second dimension has length 1
+ if y_train.shape[1] > 1 and model != 'RF':
+ raise ae.WORCValueError(f'Model {model} is not suitable for multiclass classification. Please use RF or do not use SelectFromModel.')
+
# Prefit model
selectestimator.fit(X_train, y_train)
@@ -1133,6 +1139,8 @@ Source code for WORC.classification.fitandscore
<
'RFmin_samples_split',
'RFmax_depth',
'LRpenalty',
+ 'LR_l1_ratio',
+ 'LR_solver',
'LRC',
'LDA_solver',
'LDA_shrinkage',
diff --git a/WORC/doc/_build/html/_modules/WORC/classification/metrics.html b/WORC/doc/_build/html/_modules/WORC/classification/metrics.html
index 249ebde5..7f960555 100644
--- a/WORC/doc/_build/html/_modules/WORC/classification/metrics.html
+++ b/WORC/doc/_build/html/_modules/WORC/classification/metrics.html
@@ -8,7 +8,7 @@
- WORC.classification.metrics — WORC 3.4.2 documentation
+ WORC.classification.metrics — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/classification/parameter_optimization.html b/WORC/doc/_build/html/_modules/WORC/classification/parameter_optimization.html
index fe3f54d3..fb17b7d1 100644
--- a/WORC/doc/_build/html/_modules/WORC/classification/parameter_optimization.html
+++ b/WORC/doc/_build/html/_modules/WORC/classification/parameter_optimization.html
@@ -8,7 +8,7 @@
- WORC.classification.parameter_optimization — WORC 3.4.2 documentation
+ WORC.classification.parameter_optimization — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/classification/trainclassifier.html b/WORC/doc/_build/html/_modules/WORC/classification/trainclassifier.html
index 2b7377cf..bf3adfd2 100644
--- a/WORC/doc/_build/html/_modules/WORC/classification/trainclassifier.html
+++ b/WORC/doc/_build/html/_modules/WORC/classification/trainclassifier.html
@@ -8,7 +8,7 @@
- WORC.classification.trainclassifier — WORC 3.4.2 documentation
+ WORC.classification.trainclassifier — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/detectors/detectors.html b/WORC/doc/_build/html/_modules/WORC/detectors/detectors.html
index 36b2a40e..b420e204 100644
--- a/WORC/doc/_build/html/_modules/WORC/detectors/detectors.html
+++ b/WORC/doc/_build/html/_modules/WORC/detectors/detectors.html
@@ -8,7 +8,7 @@
- WORC.detectors.detectors — WORC 3.4.2 documentation
+ WORC.detectors.detectors — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/exampledata/datadownloader.html b/WORC/doc/_build/html/_modules/WORC/exampledata/datadownloader.html
index d6f3c75a..5854d271 100644
--- a/WORC/doc/_build/html/_modules/WORC/exampledata/datadownloader.html
+++ b/WORC/doc/_build/html/_modules/WORC/exampledata/datadownloader.html
@@ -8,7 +8,7 @@
- WORC.exampledata.datadownloader — WORC 3.4.2 documentation
+ WORC.exampledata.datadownloader — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/featureprocessing/Imputer.html b/WORC/doc/_build/html/_modules/WORC/featureprocessing/Imputer.html
index fc0e437d..c4f2363c 100644
--- a/WORC/doc/_build/html/_modules/WORC/featureprocessing/Imputer.html
+++ b/WORC/doc/_build/html/_modules/WORC/featureprocessing/Imputer.html
@@ -8,7 +8,7 @@
- WORC.featureprocessing.Imputer — WORC 3.4.2 documentation
+ WORC.featureprocessing.Imputer — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/featureprocessing/Relief.html b/WORC/doc/_build/html/_modules/WORC/featureprocessing/Relief.html
index 0a653930..4add0057 100644
--- a/WORC/doc/_build/html/_modules/WORC/featureprocessing/Relief.html
+++ b/WORC/doc/_build/html/_modules/WORC/featureprocessing/Relief.html
@@ -8,7 +8,7 @@
- WORC.featureprocessing.Relief — WORC 3.4.2 documentation
+ WORC.featureprocessing.Relief — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/featureprocessing/SelectGroups.html b/WORC/doc/_build/html/_modules/WORC/featureprocessing/SelectGroups.html
index 06082e39..e2cfa1e9 100644
--- a/WORC/doc/_build/html/_modules/WORC/featureprocessing/SelectGroups.html
+++ b/WORC/doc/_build/html/_modules/WORC/featureprocessing/SelectGroups.html
@@ -8,7 +8,7 @@
- WORC.featureprocessing.SelectGroups — WORC 3.4.2 documentation
+ WORC.featureprocessing.SelectGroups — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/featureprocessing/SelectIndividuals.html b/WORC/doc/_build/html/_modules/WORC/featureprocessing/SelectIndividuals.html
index 749ece2c..f428b473 100644
--- a/WORC/doc/_build/html/_modules/WORC/featureprocessing/SelectIndividuals.html
+++ b/WORC/doc/_build/html/_modules/WORC/featureprocessing/SelectIndividuals.html
@@ -8,7 +8,7 @@
- WORC.featureprocessing.SelectIndividuals — WORC 3.4.2 documentation
+ WORC.featureprocessing.SelectIndividuals — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/featureprocessing/StatisticalTestFeatures.html b/WORC/doc/_build/html/_modules/WORC/featureprocessing/StatisticalTestFeatures.html
index fde8914b..26d45990 100644
--- a/WORC/doc/_build/html/_modules/WORC/featureprocessing/StatisticalTestFeatures.html
+++ b/WORC/doc/_build/html/_modules/WORC/featureprocessing/StatisticalTestFeatures.html
@@ -8,7 +8,7 @@
- WORC.featureprocessing.StatisticalTestFeatures — WORC 3.4.2 documentation
+ WORC.featureprocessing.StatisticalTestFeatures — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
@@ -273,7 +273,7 @@ Source code for WORC.featureprocessing.StatisticalTestFeatures
header = list()
subheader = list()
for i_name in label_name:
- header.append(str(i_name[0]))
+ header.append(str(i_name))
header.append('')
header.append('')
header.append('')
diff --git a/WORC/doc/_build/html/_modules/WORC/featureprocessing/StatisticalTestThreshold.html b/WORC/doc/_build/html/_modules/WORC/featureprocessing/StatisticalTestThreshold.html
index 8e6c55d5..9ad3840e 100644
--- a/WORC/doc/_build/html/_modules/WORC/featureprocessing/StatisticalTestThreshold.html
+++ b/WORC/doc/_build/html/_modules/WORC/featureprocessing/StatisticalTestThreshold.html
@@ -8,7 +8,7 @@
- WORC.featureprocessing.StatisticalTestThreshold — WORC 3.4.2 documentation
+ WORC.featureprocessing.StatisticalTestThreshold — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/featureprocessing/VarianceThreshold.html b/WORC/doc/_build/html/_modules/WORC/featureprocessing/VarianceThreshold.html
index 21eb34d3..0ad6b596 100644
--- a/WORC/doc/_build/html/_modules/WORC/featureprocessing/VarianceThreshold.html
+++ b/WORC/doc/_build/html/_modules/WORC/featureprocessing/VarianceThreshold.html
@@ -8,7 +8,7 @@
- WORC.featureprocessing.VarianceThreshold — WORC 3.4.2 documentation
+ WORC.featureprocessing.VarianceThreshold — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/plotting/compute_CI.html b/WORC/doc/_build/html/_modules/WORC/plotting/compute_CI.html
index e66a8eb6..1affdc67 100644
--- a/WORC/doc/_build/html/_modules/WORC/plotting/compute_CI.html
+++ b/WORC/doc/_build/html/_modules/WORC/plotting/compute_CI.html
@@ -8,7 +8,7 @@
- WORC.plotting.compute_CI — WORC 3.4.2 documentation
+ WORC.plotting.compute_CI — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/plotting/linstretch.html b/WORC/doc/_build/html/_modules/WORC/plotting/linstretch.html
index c09ed18b..0e20769f 100644
--- a/WORC/doc/_build/html/_modules/WORC/plotting/linstretch.html
+++ b/WORC/doc/_build/html/_modules/WORC/plotting/linstretch.html
@@ -8,7 +8,7 @@
- WORC.plotting.linstretch — WORC 3.4.2 documentation
+ WORC.plotting.linstretch — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/plotting/plot_ROC.html b/WORC/doc/_build/html/_modules/WORC/plotting/plot_ROC.html
index 5988eda7..c32b0b4d 100644
--- a/WORC/doc/_build/html/_modules/WORC/plotting/plot_ROC.html
+++ b/WORC/doc/_build/html/_modules/WORC/plotting/plot_ROC.html
@@ -8,7 +8,7 @@
- WORC.plotting.plot_ROC — WORC 3.4.2 documentation
+ WORC.plotting.plot_ROC — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
@@ -776,6 +776,10 @@ Source code for WORC.plotting.plot_ROC
if label_type is None:
# Assume we want to have the first key
label_type = prediction.keys()[0]
+ elif len(label_type.split(',')) != 1:
+ # Multiclass, just take the prediction label
+ label_type = prediction.keys()[0]
+
N_1 = len(prediction[label_type].Y_train[0])
N_2 = len(prediction[label_type].Y_test[0])
diff --git a/WORC/doc/_build/html/_modules/WORC/plotting/plot_barchart.html b/WORC/doc/_build/html/_modules/WORC/plotting/plot_barchart.html
index 341cdcdc..977cbaaf 100644
--- a/WORC/doc/_build/html/_modules/WORC/plotting/plot_barchart.html
+++ b/WORC/doc/_build/html/_modules/WORC/plotting/plot_barchart.html
@@ -8,7 +8,7 @@
- WORC.plotting.plot_barchart — WORC 3.4.2 documentation
+ WORC.plotting.plot_barchart — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
@@ -232,7 +232,11 @@ Source code for WORC.plotting.plot_barchart
if label_type is None:
label_type = keys[0]
- prediction = prediction[label_type]
+ try:
+ prediction = prediction[label_type]
+ except KeyError:
+ # Multiclass reroute
+ prediction = prediction[keys[0]]
# Extract the parameter settings:
parameters = dict()
diff --git a/WORC/doc/_build/html/_modules/WORC/plotting/plot_images.html b/WORC/doc/_build/html/_modules/WORC/plotting/plot_images.html
index 1e73883e..0bf577ea 100644
--- a/WORC/doc/_build/html/_modules/WORC/plotting/plot_images.html
+++ b/WORC/doc/_build/html/_modules/WORC/plotting/plot_images.html
@@ -8,7 +8,7 @@
- WORC.plotting.plot_images — WORC 3.4.2 documentation
+ WORC.plotting.plot_images — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/plotting/plot_ranked_scores.html b/WORC/doc/_build/html/_modules/WORC/plotting/plot_ranked_scores.html
index 8048a6f1..46eef16b 100644
--- a/WORC/doc/_build/html/_modules/WORC/plotting/plot_ranked_scores.html
+++ b/WORC/doc/_build/html/_modules/WORC/plotting/plot_ranked_scores.html
@@ -8,7 +8,7 @@
- WORC.plotting.plot_ranked_scores — WORC 3.4.2 documentation
+ WORC.plotting.plot_ranked_scores — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
@@ -285,7 +285,6 @@ Source code for WORC.plotting.plot_ranked_scores
# Read the inputs
prediction = pd.read_hdf(estimator)
- label_type = prediction.keys()[0] # NOTE: Assume we want to have the first key
# Determine the predicted score per patient
print('Determining score per patient.')
@@ -435,49 +434,107 @@ Source code for WORC.plotting.plot_ranked_scores
scores = dict()
truths = dict()
- y_truths_flat = flatten_object(y_truths)
- y_scores_flat = flatten_object(y_scores)
- PIDs_scores_flat = flatten_object(PIDs_scores)
+ def aggregate_scores(y_truths_in, y_scores_in, PIDs_scores_in):
+ y_truths_flat = flatten_object(y_truths_in)
+ y_scores_flat = flatten_object(y_scores_in)
+ PIDs_scores_flat = flatten_object(PIDs_scores_in)
+
+ for yt, ys, pid in zip(y_truths_flat, y_scores_flat, PIDs_scores_flat):
+ if pid not in scores.keys():
+ # No scores yet for patient, create list
+ scores[pid] = list()
+ truths[pid] = yt
+ scores[pid].append(ys)
+
+ # Take the mean for each patient and rank them
+ scores_means = {pid: np.mean(scores[pid]) for pid in scores.keys()}
+
+ # Rank according to mean scores
+ ranking = np.argsort(list(scores_means.values()))
+ ranked_PIDs = [list(scores_means.keys())[r] for r in ranking]
+
+ ranked_mean_scores = [scores_means[r] for r in ranked_PIDs]
+ ranked_scores = [scores[r] for r in ranked_PIDs]
+ ranked_truths = [truths[r] for r in ranked_PIDs]
+ return ranked_PIDs, ranked_truths, ranked_mean_scores, ranked_scores
+
+ # Gather ground truth for each pid
+ pid_truths = dict()
+ for y, p in zip(y_truths, PIDs_scores):
+ for k, v in zip(p, y):
+ pid_truths[k] = v
+
+ if len(label_type.split(',')) != 1:
+ # Multiclass
+ ranked_PIDs = dict()
+ ranked_truths = dict()
+ ranked_mean_scores = dict()
+ ranked_scores = dict()
+ total_scores = list()
+ means = list()
+ for lnum, label in enumerate(label_type.split(',')):
+ # Select only values for this label
+ y_truths_thislabel = np.asarray(y_truths)[:, :, lnum]
+ y_scores_thislabel = np.asarray(y_scores)[:, :, lnum]
+
+ # Rank the patients and scores
+ ranked_PIDs_label, ranked_truths_label, ranked_mean_scores_label, ranked_scores_label =\
+ aggregate_scores(y_truths_thislabel, y_scores_thislabel, PIDs_scores)
+
+ ranked_PIDs[label] = ranked_PIDs_label
+ ranked_truths[label] = ranked_truths_label
+ ranked_mean_scores[label] = ranked_mean_scores_label
+ ranked_scores[label] = ranked_scores_label
+
+ means.append(f"Mean_{label}")
+ total_scores.extend([f"Score_{label}_{i}" for i in range(max([len(score) for score in ranked_scores_label]))])
+
+ # Write output to csv
+ unique_pids = list(set(flatten_object(PIDs_scores)))
+ # FIXME: bug in scores, so only give the means
+ if output_csv is not None:
+ print("Writing output scores to CSV.")
+ header = ['PatientID', 'TrueLabel', 'Predicted'] + means #+ total_scores
- for yt, ys, pid in zip(y_truths_flat, y_scores_flat, PIDs_scores_flat):
- if pid not in scores.keys():
- # No scores yet for patient, create list
- scores[pid] = list()
- truths[pid] = yt
- scores[pid].append(ys)
-
- # Take the mean for each patient and rank them
- scores_means = dict()
- maxlen = 0
- for pid in scores.keys():
- scores_means[pid] = np.mean(scores[pid])
- if len(scores[pid]) > maxlen:
- maxlen = len(scores[pid])
+ with open(output_csv, 'w') as csv_file:
+ writer = csv.writer(csv_file)
+ writer.writerow(header)
- ranking = np.argsort(list(scores_means.values()))
- ranked_PIDs = [list(scores_means.keys())[r] for r in ranking]
+ for pid in unique_pids:
+ pid_means = list()
+ pid_truth = pid_truths[pid]
+ pid_scores = list()
+ for lnum, label in enumerate(label_type.split(',')):
+ p_index = ranked_PIDs[label].index(pid)
+ pid_means.append(ranked_mean_scores[label][p_index])
+ pid_scores.extend(ranked_scores[label][p_index])
- ranked_mean_scores = [scores_means[r] for r in ranked_PIDs]
- ranked_scores = [scores[r] for r in ranked_PIDs]
- ranked_truths = [truths[r] for r in ranked_PIDs]
+ towrite = [pid, str(pid_truth), np.argmax(pid_means)] + pid_means #+ pid_scores
+ writer.writerow(towrite)
- # Write output to csv
- if output_csv is not None:
- print("Writing output scores to CSV.")
- header = ['PatientID', 'TrueLabel', 'Probability']
- for i in range(0, maxlen):
- header.append('Score' + str(i+1))
+ else:
+ # Single Label
+ ranked_PIDs, ranked_truths, ranked_mean_scores, ranked_scores =\
+ aggregate_scores(y_truths, y_scores, PIDs_scores)
+
+ # Write output to csv
+ maxlen = max([len(score) for score in scores.values()])
+ if output_csv is not None:
+ print("Writing output scores to CSV.")
+ header = ['PatientID', 'TrueLabel', 'Probability']
+ for i in range(0, maxlen):
+ header.append('Score' + str(i+1))
- with open(output_csv, 'w') as csv_file:
- writer = csv.writer(csv_file)
- writer.writerow(header)
+ with open(output_csv, 'w') as csv_file:
+ writer = csv.writer(csv_file)
+ writer.writerow(header)
- for pid, truth, smean, scores in zip(ranked_PIDs, ranked_truths, ranked_mean_scores, ranked_scores):
- towrite = [str(pid), str(truth), str(smean)]
- for s in scores:
- towrite.append(str(s))
+ for pid, truth, smean, scores in zip(ranked_PIDs, ranked_truths, ranked_mean_scores, ranked_scores):
+ towrite = [str(pid), str(truth), str(smean)]
+ for s in scores:
+ towrite.append(str(s))
- writer.writerow(towrite)
+ writer.writerow(towrite)
return ranked_mean_scores, ranked_truths, ranked_PIDs
@@ -545,7 +602,7 @@ Source code for WORC.plotting.plot_ranked_scores
ensemble=ensemble,
output_csv=output_csv)
elif scores == 'percentages':
- if prediction[label_type].config['CrossValidation']['Type'] == 'LOO':
+ if prediction[prediction.keys()[0]].config['CrossValidation']['Type'] == 'LOO':
print('Cannot rank percentages for LOO, returning dummies.')
ranked_scores = ranked_truths = ranked_PIDs = []
with open(output_csv, 'w') as csv_file:
@@ -563,35 +620,41 @@ Source code for WORC.plotting.plot_ranked_scores
raise WORCKeyError(message)
if output_zip is not None or output_itk is not None:
- # Rerank the scores split per ground truth class: negative for 0, positive for 1
- ranked_scores_temp = list()
- for l, p in zip(ranked_truths, ranked_scores):
- if l == 0:
- ranked_scores_temp.append(-p)
- else:
- ranked_scores_temp.append(p)
-
- ranked_scores = ranked_scores_temp
- ranking = np.argsort(ranked_scores)
- ranked_scores = [ranked_scores[r] for r in ranking]
- ranked_truths = [ranked_truths[r] for r in ranking]
- ranked_PIDs = [ranked_PIDs[r] for r in ranking]
+ # FIXME: check for multilabel by checking type
+ if type(ranked_scores) == list():
+ # Rerank the scores split per ground truth class: negative for 0, positive for 1
+ ranked_scores_temp = list()
+ for l, p in zip(ranked_truths, ranked_scores):
+ if l == 0:
+ ranked_scores_temp.append(-p)
+ else:
+ ranked_scores_temp.append(p)
- # Convert to lower to later on overcome matching errors
- ranked_PIDs = [i.lower() for i in ranked_PIDs]
+ ranked_scores = ranked_scores_temp
+ ranking = np.argsort(ranked_scores)
+ ranked_scores = [ranked_scores[r] for r in ranking]
+ ranked_truths = [ranked_truths[r] for r in ranking]
+ ranked_PIDs = [ranked_PIDs[r] for r in ranking]
- if images:
- plot_ranked_images(pinfo=pinfo,
- label_type=label_type,
- images=images,
- segmentations=segmentations,
- ranked_truths=ranked_truths,
- ranked_scores=ranked_scores,
- ranked_PIDs=ranked_PIDs,
- output_zip=output_zip,
- output_itk=output_itk,
- scores=scores)
+ # Convert to lower to later on overcome matching errors
+ ranked_PIDs = [i.lower() for i in ranked_PIDs]
+ if images:
+ plot_ranked_images(pinfo=pinfo,
+ label_type=label_type,
+ images=images,
+ segmentations=segmentations,
+ ranked_truths=ranked_truths,
+ ranked_scores=ranked_scores,
+ ranked_PIDs=ranked_PIDs,
+ output_zip=output_zip,
+ output_itk=output_itk,
+ scores=scores)
+ else:
+ # Make dummy
+ if output_zip is not None:
+ zipfile.ZipFile(output_zip,
+ 'w', zipfile.ZIP_DEFLATED, allowZip64=True)
[docs]def example():
case = 'MESFIB'
@@ -692,7 +755,12 @@ Source code for WORC.plotting.plot_ranked_scores
ranked_scores=ranked_scores,
ranked_PIDs=ranked_PIDs,
output_zip=output_zip,
- scores=scores)
+ scores=scores)
+ else:
+ # Make dummy
+ if output_zip is not None:
+ zipfile.ZipFile(output_zip,
+ 'w', zipfile.ZIP_DEFLATED, allowZip64=True)
if __name__ == '__main__':
diff --git a/WORC/doc/_build/html/_modules/WORC/plotting/scatterplot.html b/WORC/doc/_build/html/_modules/WORC/plotting/scatterplot.html
index 3e4d5d96..e8c4be28 100644
--- a/WORC/doc/_build/html/_modules/WORC/plotting/scatterplot.html
+++ b/WORC/doc/_build/html/_modules/WORC/plotting/scatterplot.html
@@ -8,7 +8,7 @@
- WORC.plotting.scatterplot — WORC 3.4.2 documentation
+ WORC.plotting.scatterplot — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/processing/ExtractNLargestBlobsn.html b/WORC/doc/_build/html/_modules/WORC/processing/ExtractNLargestBlobsn.html
index f565344f..9e845400 100644
--- a/WORC/doc/_build/html/_modules/WORC/processing/ExtractNLargestBlobsn.html
+++ b/WORC/doc/_build/html/_modules/WORC/processing/ExtractNLargestBlobsn.html
@@ -8,7 +8,7 @@
- WORC.processing.ExtractNLargestBlobsn — WORC 3.4.2 documentation
+ WORC.processing.ExtractNLargestBlobsn — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/processing/classes.html b/WORC/doc/_build/html/_modules/WORC/processing/classes.html
index 18cea5d9..d5926857 100644
--- a/WORC/doc/_build/html/_modules/WORC/processing/classes.html
+++ b/WORC/doc/_build/html/_modules/WORC/processing/classes.html
@@ -8,7 +8,7 @@
- WORC.processing.classes — WORC 3.4.2 documentation
+ WORC.processing.classes — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/processing/label_processing.html b/WORC/doc/_build/html/_modules/WORC/processing/label_processing.html
index 021457f9..b0e6bb8c 100644
--- a/WORC/doc/_build/html/_modules/WORC/processing/label_processing.html
+++ b/WORC/doc/_build/html/_modules/WORC/processing/label_processing.html
@@ -8,7 +8,7 @@
- WORC.processing.label_processing — WORC 3.4.2 documentation
+ WORC.processing.label_processing — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/resources/fastr_tests/CalcFeatures_test.html b/WORC/doc/_build/html/_modules/WORC/resources/fastr_tests/CalcFeatures_test.html
index 24d11ac5..2786ef8d 100644
--- a/WORC/doc/_build/html/_modules/WORC/resources/fastr_tests/CalcFeatures_test.html
+++ b/WORC/doc/_build/html/_modules/WORC/resources/fastr_tests/CalcFeatures_test.html
@@ -8,7 +8,7 @@
- WORC.resources.fastr_tests.CalcFeatures_test — WORC 3.4.2 documentation
+ WORC.resources.fastr_tests.CalcFeatures_test — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/resources/fastr_tests/elastix_test.html b/WORC/doc/_build/html/_modules/WORC/resources/fastr_tests/elastix_test.html
index 96eccd95..83b37df0 100644
--- a/WORC/doc/_build/html/_modules/WORC/resources/fastr_tests/elastix_test.html
+++ b/WORC/doc/_build/html/_modules/WORC/resources/fastr_tests/elastix_test.html
@@ -8,7 +8,7 @@
- WORC.resources.fastr_tests.elastix_test — WORC 3.4.2 documentation
+ WORC.resources.fastr_tests.elastix_test — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/resources/fastr_tests/segmentix_test.html b/WORC/doc/_build/html/_modules/WORC/resources/fastr_tests/segmentix_test.html
index b3ae104d..711a6cd1 100644
--- a/WORC/doc/_build/html/_modules/WORC/resources/fastr_tests/segmentix_test.html
+++ b/WORC/doc/_build/html/_modules/WORC/resources/fastr_tests/segmentix_test.html
@@ -8,7 +8,7 @@
- WORC.resources.fastr_tests.segmentix_test — WORC 3.4.2 documentation
+ WORC.resources.fastr_tests.segmentix_test — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/tools/Elastix.html b/WORC/doc/_build/html/_modules/WORC/tools/Elastix.html
index 5955d50d..e7cdbede 100644
--- a/WORC/doc/_build/html/_modules/WORC/tools/Elastix.html
+++ b/WORC/doc/_build/html/_modules/WORC/tools/Elastix.html
@@ -8,7 +8,7 @@
- WORC.tools.Elastix — WORC 3.4.2 documentation
+ WORC.tools.Elastix — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/tools/Evaluate.html b/WORC/doc/_build/html/_modules/WORC/tools/Evaluate.html
index b21014c8..c5b8f9a5 100644
--- a/WORC/doc/_build/html/_modules/WORC/tools/Evaluate.html
+++ b/WORC/doc/_build/html/_modules/WORC/tools/Evaluate.html
@@ -8,7 +8,7 @@
- WORC.tools.Evaluate — WORC 3.4.2 documentation
+ WORC.tools.Evaluate — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
@@ -190,7 +190,7 @@ Source code for WORC.tools.Evaluate
[docs]class Evaluate(object):
"""Build a network that evaluates the performance of an estimator."""
-[docs] def __init__(self, label_type, modus='classification', ensemble=50,
+[docs] def __init__(self, label_type, modus='binary_classification', ensemble=50,
scores='percentages',
parent=None, features=None,
fastr_plugin='LinearExecution',
@@ -232,7 +232,7 @@ Source code for WORC.tools.Evaluate
[docs] def create_network(self):
"""Add evaluate components to network."""
# Create all nodes
- if self.modus == 'classification':
+ if self.modus == 'binary_classification':
self.node_ROC =\
self.network.create_node('worc/PlotROC:1.0', tool_version='1.0',
id='plot_ROC',
@@ -257,7 +257,7 @@ Source code for WORC.tools.Evaluate
resources=ResourceLimit(memory='6G'),
step_id='Evaluation')
- if self.modus == 'classification':
+ if 'classification' in self.modus:
self.node_STest =\
self.network.create_node('worc/StatisticalTestFeatures:1.0',
tool_version='1.0',
@@ -294,7 +294,7 @@ Source code for WORC.tools.Evaluate
step_id='Evaluation')
# Create sinks
- if self.modus == 'classification':
+ if self.modus == 'binary_classification':
self.sink_ROC_PNG =\
self.network.create_sink('PNGFile', id='ROC_PNG',
step_id='general_sinks')
@@ -332,7 +332,7 @@ Source code for WORC.tools.Evaluate
self.network.create_sink('CSVFile', id='Hyperparameters_CSV',
step_id='general_sinks')
- if self.modus == 'classification':
+ if 'classification' in self.modus:
self.sink_STest_CSV =\
self.network.create_sink('CSVFile',
id='StatisticalTestFeatures_CSV',
@@ -373,7 +373,7 @@ Source code for WORC.tools.Evaluate
step_id='general_sinks')
# Create links to sinks
- if self.modus == 'classification':
+ if self.modus == 'binary_classification':
self.sink_ROC_PNG.input = self.node_ROC.outputs['ROC_png']
self.sink_ROC_Tex.input = self.node_ROC.outputs['ROC_tex']
self.sink_ROC_CSV.input = self.node_ROC.outputs['ROC_csv']
@@ -390,7 +390,7 @@ Source code for WORC.tools.Evaluate
self.sink_Hyperparameters_CSV.input = self.node_Hyperparameters.outputs['output_csv']
- if self.modus == 'classification':
+ if 'classification' in self.modus:
self.sink_STest_CSV.input = self.node_STest.outputs['output_csv']
self.sink_STest_PNG.input = self.node_STest.outputs['output_png']
self.sink_STest_Tex.input = self.node_STest.outputs['output_tex']
@@ -457,7 +457,7 @@ Source code for WORC.tools.Evaluate
[docs] def create_links_Standalone(self):
"""Create links in network between nodes when using standalone."""
# Sources from the Evaluate network are used
- if self.modus == 'classification':
+ if self.modus == 'binary_classification':
self.node_ROC.inputs['prediction'] = self.source_Estimator.output
self.node_ROC.inputs['pinfo'] = self.source_PatientInfo.output
@@ -468,13 +468,13 @@ Source code for WORC.tools.Evaluate
self.node_Hyperparameters.inputs['prediction'] = self.source_Estimator.output
- if self.modus == 'classification':
+ if 'classification' in self.modus:
self.links_STest_Features = list()
self.links_decomposition_Features = list()
self.links_Boxplots_Features = list()
for idx, label in enumerate(self.labels):
- if self.modus == 'classification':
+ if 'classification' in self.modus:
self.links_STest_Features.append(self.node_STest.inputs['features'][str(label)] << self.source_Features[idx].output)
self.links_STest_Features[idx].collapse = 'features'
@@ -484,7 +484,7 @@ Source code for WORC.tools.Evaluate
self.links_Boxplots_Features.append(self.node_Boxplots_Features.inputs['features'][str(label)] << self.source_Features[idx].output)
self.links_Boxplots_Features[idx].collapse = 'features'
- if self.modus == 'classification':
+ if 'classification' in self.modus:
self.node_STest.inputs['patientclass'] = self.source_PatientInfo.output
self.node_STest.inputs['config'] = self.source_Config.output
@@ -498,7 +498,6 @@ Source code for WORC.tools.Evaluate
self.link_segmentations_perc = self.network.create_link(self.source_Segmentations.output, self.node_Ranked_Percentages.inputs['segmentations'])
self.link_segmentations_perc.collapse = 'patients'
-
self.node_Boxplots_Features.inputs['patientclass'] = self.source_PatientInfo.output
self.node_Boxplots_Features.inputs['config'] = self.source_Config.output
@@ -509,10 +508,11 @@ Source code for WORC.tools.Evaluate
self.link_segmentations_post = self.network.create_link(self.source_Segmentations.output, self.node_Ranked_Posteriors.inputs['segmentations'])
self.link_segmentations_post.collapse = 'patients'
- if self.modus == 'classification':
+ if self.modus == 'binary_classification':
self.node_ROC.inputs['ensemble'] = self.source_Ensemble.output
self.node_ROC.inputs['label_type'] = self.source_LabelType.output
+ if 'classification' in self.modus:
self.node_Ranked_Percentages.inputs['ensemble'] =\
self.source_Ensemble.output
self.node_Ranked_Percentages.inputs['label_type'] =\
@@ -551,10 +551,11 @@ Source code for WORC.tools.Evaluate
segmentations =\
self.parent.sources_segmentations_train[label].output
- if self.modus == 'classification':
+ if self.modus == 'binary_classification':
self.node_ROC.inputs['ensemble'] = self.parent.source_Ensemble.output
self.node_ROC.inputs['label_type'] = self.parent.source_LabelType.output
+ if 'classification' in self.modus:
self.node_Ranked_Percentages.inputs['ensemble'] =\
self.parent.source_Ensemble.output
self.node_Ranked_Percentages.inputs['label_type'] =\
@@ -571,7 +572,7 @@ Source code for WORC.tools.Evaluate
self.node_Ranked_Posteriors.inputs['label_type'] =\
self.parent.source_LabelType.output
- if self.modus == 'classification':
+ if self.modus == 'binary_classification':
self.node_ROC.inputs['prediction'] = prediction
self.node_ROC.inputs['pinfo'] = pinfo
@@ -579,7 +580,7 @@ Source code for WORC.tools.Evaluate
self.node_Hyperparameters.inputs['prediction'] = prediction
- if self.modus == 'classification':
+ if 'classification' in self.modus:
self.links_STest_Features = dict()
self.links_decomposition_Features = dict()
@@ -589,7 +590,7 @@ Source code for WORC.tools.Evaluate
if self.parent.configs[0]['General']['ComBat'] == 'True':
name = 'ComBat'
# Take features from ComBat
- if self.modus == 'classification':
+ if 'classification' in self.modus:
self.links_STest_Features[name] =\
self.network.create_link(self.parent.ComBat.outputs['features_train_out'], self.node_STest.inputs['features'])
@@ -600,7 +601,7 @@ Source code for WORC.tools.Evaluate
self.network.create_link(self.parent.ComBat.outputs['features_train_out'], self.node_Boxplots_Features.inputs['features'])
# All features should be input at once
- if self.modus == 'classification':
+ if 'classification' in self.modus:
self.links_STest_Features[name].collapse = 'ComBat'
self.links_decomposition_Features[name].collapse = 'ComBat'
@@ -614,7 +615,7 @@ Source code for WORC.tools.Evaluate
# Take features directly from feature computation toolboxes
for node in self.parent.featureconverter_train[label]:
name = node.id
- if self.modus == 'classification':
+ if 'classification' in self.modus:
self.links_STest_Features[name] =\
self.node_STest.inputs['features'][name] << node.outputs['feat_out']
@@ -625,7 +626,7 @@ Source code for WORC.tools.Evaluate
self.node_Boxplots_Features.inputs['features'][name] << node.outputs['feat_out']
# All features should be input at once
- if self.modus == 'classification':
+ if 'classification' in self.modus:
self.links_STest_Features[name].collapse = 'train'
self.links_decomposition_Features[name].collapse = 'train'
@@ -634,7 +635,7 @@ Source code for WORC.tools.Evaluate
# Feature are precomputed and given as sources
for node in self.parent.sources_features_train.values():
name = node.id
- if self.modus == 'classification':
+ if 'classification' in self.modus:
self.links_STest_Features[name] =\
self.node_STest.inputs['features'][name] << node.output
@@ -644,7 +645,7 @@ Source code for WORC.tools.Evaluate
self.node_Boxplots_Features.inputs['features'][name] << node.output
# All features should be input at once
- if self.modus == 'classification':
+ if 'classification' in self.modus:
self.links_STest_Features[name].collapse = 'train'
self.links_decomposition_Features[name].collapse = 'train'
@@ -654,7 +655,7 @@ Source code for WORC.tools.Evaluate
# Feature are precomputed and given as sources
for node in self.parent.sources_features_train.values():
name = node.id
- if self.modus == 'classification':
+ if 'classification' in self.modus:
self.links_STest_Features[name] =\
self.node_STest.inputs['features'][name] << node.output
self.links_decomposition_Features[name] =\
@@ -664,13 +665,13 @@ Source code for WORC.tools.Evaluate
self.node_Boxplots_Features.inputs['features'][name] << node.output
# All features should be input at once
- if self.modus == 'classification':
+ if 'classification' in self.modus:
self.links_STest_Features[name].collapse = 'train'
self.links_decomposition_Features[name].collapse = 'train'
self.links_Boxplots_Features[name].collapse = 'train'
- if self.modus == 'classification':
+ if 'classification' in self.modus:
self.node_STest.inputs['patientclass'] = pinfo
self.node_STest.inputs['config'] = config
@@ -691,7 +692,7 @@ Source code for WORC.tools.Evaluate
segmentations =\
self.parent.sources_segmentations_test[label].output
- if self.modus == 'classification':
+ if 'classification' in self.modus:
self.link_images_perc =\
self.network.create_link(images, self.node_Ranked_Percentages.inputs['images'])
self.link_images_perc.collapse = 'test'
@@ -708,7 +709,7 @@ Source code for WORC.tools.Evaluate
elif hasattr(self.parent, 'sources_images_train'):
if self.parent.sources_images_train:
- if self.modus == 'classification':
+ if 'classification' in self.modus:
self.link_images_perc =\
self.network.create_link(images, self.node_Ranked_Percentages.inputs['images'])
self.link_images_perc.collapse = 'train'
@@ -744,7 +745,7 @@ Source code for WORC.tools.Evaluate
else:
self.sink_data = self.parent.sink_data
- if self.modus == 'classification':
+ if self.modus == 'binary_classification':
if 'ROC_PNG' not in sink_data.keys():
self.sink_data['ROC_PNG'] = ("vfs://output/{}/Evaluation/ROC_{{sample_id}}_{{cardinality}}{{ext}}").format(self.name)
if 'ROC_Tex' not in sink_data.keys():
@@ -769,7 +770,7 @@ Source code for WORC.tools.Evaluate
if 'Hyperparameters_CSV' not in sink_data.keys():
self.sink_data['Hyperparameters_CSV'] = ("vfs://output/{}/Evaluation/Hyperparameters_{{sample_id}}_{{cardinality}}{{ext}}").format(self.name)
- if self.modus == 'classification':
+ if 'classification' in self.modus:
if 'StatisticalTestFeatures_CSV' not in sink_data.keys():
self.sink_data['StatisticalTestFeatures_CSV'] = ("vfs://output/{}/Evaluation/StatisticalTestFeatures_{{sample_id}}_{{cardinality}}{{ext}}").format(self.name)
diff --git a/WORC/doc/_build/html/_modules/WORC/tools/Slicer.html b/WORC/doc/_build/html/_modules/WORC/tools/Slicer.html
index a9cab5c1..397ffdf4 100644
--- a/WORC/doc/_build/html/_modules/WORC/tools/Slicer.html
+++ b/WORC/doc/_build/html/_modules/WORC/tools/Slicer.html
@@ -8,7 +8,7 @@
- WORC.tools.Slicer — WORC 3.4.2 documentation
+ WORC.tools.Slicer — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/tools/Transformix.html b/WORC/doc/_build/html/_modules/WORC/tools/Transformix.html
index 5ebf9dbe..20aa2c0a 100644
--- a/WORC/doc/_build/html/_modules/WORC/tools/Transformix.html
+++ b/WORC/doc/_build/html/_modules/WORC/tools/Transformix.html
@@ -8,7 +8,7 @@
- WORC.tools.Transformix — WORC 3.4.2 documentation
+ WORC.tools.Transformix — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/WORC/tools/createfixedsplits.html b/WORC/doc/_build/html/_modules/WORC/tools/createfixedsplits.html
index cbc9352d..54c57e77 100644
--- a/WORC/doc/_build/html/_modules/WORC/tools/createfixedsplits.html
+++ b/WORC/doc/_build/html/_modules/WORC/tools/createfixedsplits.html
@@ -8,7 +8,7 @@
- WORC.tools.createfixedsplits — WORC 3.4.2 documentation
+ WORC.tools.createfixedsplits — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/_modules/index.html b/WORC/doc/_build/html/_modules/index.html
index b08b7ade..205e9050 100644
--- a/WORC/doc/_build/html/_modules/index.html
+++ b/WORC/doc/_build/html/_modules/index.html
@@ -8,7 +8,7 @@
- Overview: module code — WORC 3.4.2 documentation
+ Overview: module code — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
@@ -228,6 +228,7 @@ All modules for which code is available
WORC.resources.fastr_tests.elastix_test
WORC.resources.fastr_tests.segmentix_test
WORC.statistics.delong
+WORC.tests.WORCTutorialSimple_travis_multiclass
WORC.tests.WORCTutorialSimple_travis_regression
WORC.tests.test_combat
WORC.tests.test_helpers
diff --git a/WORC/doc/_build/html/_static/documentation_options.js b/WORC/doc/_build/html/_static/documentation_options.js
index 04328768..79dd7988 100644
--- a/WORC/doc/_build/html/_static/documentation_options.js
+++ b/WORC/doc/_build/html/_static/documentation_options.js
@@ -1,6 +1,6 @@
var DOCUMENTATION_OPTIONS = {
URL_ROOT: document.getElementById("documentation_options").getAttribute('data-url_root'),
- VERSION: '3.4.2',
+ VERSION: '3.4.3',
LANGUAGE: 'None',
COLLAPSE_INDEX: false,
FILE_SUFFIX: '.html',
diff --git a/WORC/doc/_build/html/autogen/WORC.IOparser.html b/WORC/doc/_build/html/autogen/WORC.IOparser.html
index 9e9df36f..817ff1eb 100644
--- a/WORC/doc/_build/html/autogen/WORC.IOparser.html
+++ b/WORC/doc/_build/html/autogen/WORC.IOparser.html
@@ -8,7 +8,7 @@
- IOparser Package — WORC 3.4.2 documentation
+ IOparser Package — WORC 3.4.3 documentation
@@ -64,7 +64,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/autogen/WORC.classification.html b/WORC/doc/_build/html/autogen/WORC.classification.html
index 78f08102..be50c4a5 100644
--- a/WORC/doc/_build/html/autogen/WORC.classification.html
+++ b/WORC/doc/_build/html/autogen/WORC.classification.html
@@ -8,7 +8,7 @@
- classification Package — WORC 3.4.2 documentation
+ classification Package — WORC 3.4.3 documentation
@@ -64,7 +64,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/autogen/WORC.config.html b/WORC/doc/_build/html/autogen/WORC.config.html
index 8c03634d..a1f790a6 100644
--- a/WORC/doc/_build/html/autogen/WORC.config.html
+++ b/WORC/doc/_build/html/autogen/WORC.config.html
@@ -8,7 +8,7 @@
- <no title> — WORC 3.4.2 documentation
+ <no title> — WORC 3.4.3 documentation
@@ -62,7 +62,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/autogen/WORC.detectors.html b/WORC/doc/_build/html/autogen/WORC.detectors.html
index 9a0c240c..1246e656 100644
--- a/WORC/doc/_build/html/autogen/WORC.detectors.html
+++ b/WORC/doc/_build/html/autogen/WORC.detectors.html
@@ -8,7 +8,7 @@
- detectors Package — WORC 3.4.2 documentation
+ detectors Package — WORC 3.4.3 documentation
@@ -64,7 +64,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/autogen/WORC.exampledata.html b/WORC/doc/_build/html/autogen/WORC.exampledata.html
index 76b0cba7..8b695037 100644
--- a/WORC/doc/_build/html/autogen/WORC.exampledata.html
+++ b/WORC/doc/_build/html/autogen/WORC.exampledata.html
@@ -8,7 +8,7 @@
- exampledata Package — WORC 3.4.2 documentation
+ exampledata Package — WORC 3.4.3 documentation
@@ -64,7 +64,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/autogen/WORC.facade.html b/WORC/doc/_build/html/autogen/WORC.facade.html
index 83b08a0d..86eda425 100644
--- a/WORC/doc/_build/html/autogen/WORC.facade.html
+++ b/WORC/doc/_build/html/autogen/WORC.facade.html
@@ -8,7 +8,7 @@
- facade Package — WORC 3.4.2 documentation
+ facade Package — WORC 3.4.3 documentation
@@ -64,7 +64,7 @@
- 3.4.2
+ 3.4.3
@@ -251,7 +251,7 @@
Please also see the WORCTutorial Github.
-
-
__dict__ = mappingproxy({'__module__': 'WORC.facade.simpleworc', '__doc__': 'Facade around the main WORC object for simple interaction.\n\n Please also see the `WORCTutorial Github <https://github.com/MStarmans91/WORCTutorial/>`_.\n ', '__init__': <function SimpleWORC.__init__>, 'set_fixed_splits': <function SimpleWORC.set_fixed_splits>, 'features_from_this_directory': <function SimpleWORC.features_from_this_directory>, 'images_from_this_directory': <function SimpleWORC.images_from_this_directory>, 'segmentations_from_this_directory': <function SimpleWORC.segmentations_from_this_directory>, 'labels_from_this_file': <function SimpleWORC.labels_from_this_file>, 'semantics_from_this_file': <function SimpleWORC.semantics_from_this_file>, 'predict_labels': <function SimpleWORC.predict_labels>, '_set_and_validate_estimators': <function SimpleWORC._set_and_validate_estimators>, 'count_num_subjects': <function SimpleWORC.count_num_subjects>, '_validate': <function SimpleWORC._validate>, 'execute': <function SimpleWORC.execute>, 'binary_classification': <function SimpleWORC.binary_classification>, 'regression': <function SimpleWORC.regression>, 'survival': <function SimpleWORC.survival>, 'add_config_overrides': <function SimpleWORC.add_config_overrides>, 'add_evaluation': <function SimpleWORC.add_evaluation>, 'set_tmpdir': <function SimpleWORC.set_tmpdir>, 'set_multicore_execution': <function SimpleWORC.set_multicore_execution>, 'features_from_radiomix_xlsx': <function SimpleWORC.features_from_radiomix_xlsx>, '__dict__': <attribute '__dict__' of 'SimpleWORC' objects>, '__weakref__': <attribute '__weakref__' of 'SimpleWORC' objects>})¶
+__dict__ = mappingproxy({'__module__': 'WORC.facade.simpleworc', '__doc__': 'Facade around the main WORC object for simple interaction.\n\n Please also see the `WORCTutorial Github <https://github.com/MStarmans91/WORCTutorial/>`_.\n ', '__init__': <function SimpleWORC.__init__>, 'set_fixed_splits': <function SimpleWORC.set_fixed_splits>, 'features_from_this_directory': <function SimpleWORC.features_from_this_directory>, 'images_from_this_directory': <function SimpleWORC.images_from_this_directory>, 'segmentations_from_this_directory': <function SimpleWORC.segmentations_from_this_directory>, 'masks_from_this_directory': <function SimpleWORC.masks_from_this_directory>, 'labels_from_this_file': <function SimpleWORC.labels_from_this_file>, 'semantics_from_this_file': <function SimpleWORC.semantics_from_this_file>, 'predict_labels': <function SimpleWORC.predict_labels>, '_set_and_validate_estimators': <function SimpleWORC._set_and_validate_estimators>, 'count_num_subjects': <function SimpleWORC.count_num_subjects>, '_validate': <function SimpleWORC._validate>, 'binary_classification': <function SimpleWORC.binary_classification>, 'multiclass_classification': <function SimpleWORC.multiclass_classification>, 'regression': <function SimpleWORC.regression>, 'survival': <function SimpleWORC.survival>, 'add_config_overrides': <function SimpleWORC.add_config_overrides>, 'add_evaluation': <function SimpleWORC.add_evaluation>, 'set_tmpdir': <function SimpleWORC.set_tmpdir>, 'set_multicore_execution': <function SimpleWORC.set_multicore_execution>, 'features_from_radiomix_xlsx': <function SimpleWORC.features_from_radiomix_xlsx>, 'execute': <function SimpleWORC.execute>, '__dict__': <attribute '__dict__' of 'SimpleWORC' objects>, '__weakref__': <attribute '__weakref__' of 'SimpleWORC' objects>})¶
@@ -403,6 +403,48 @@
+
+-
+
masks_from_this_directory(directory, mask_file_name='mask.nii.gz', glob='*/', is_training=True)[source]¶
+Use masks from a directory as sources in WORC.
+Masks are used in a variety of tools to ``mask’’ certain parts
+of the image, e.g. in the normalization. Masks are fully
+optional.
+SimpleWORC uses a directory glob to look for files meeting
+the requirements to include, based on the input parameters.
+Example:
+When using “directory = C:UsersMyNameMaskFolder”,
+masks_from_this_directory will include all mask.nii.gz files from all subfolders in the directory.
+
+- directory: string
Identifies the root directory in which to search for mask files.
+- mask_file_name: string, default mask.nii.gz
Name of the files which will be included. Can include wildcards (*).
+- glob: string, default */
Identify the search string to be used in the glob. Can include wildcards (*).
+- is_training: Boolean, default True
Identify whether these masks should be used in the training or test dataset.
+
+
+
+
+-
+
multiclass_classification(estimators=None, scoring_method='f1_weighted', coarse=True)[source]¶
+Tell WORC do to a multiclass classification experiment.
+
+- estimators: list
List of strings with names of valid estimators. See the
+WORC Config chapter for allowed options.
+If coarse, only an SVM will be used. If not, the default full
+config will be used.
+- scoring_method: string, default f1
Name of the scoring method used to rank the workflows. See the
+WORC Config chapter for allowed options.
+- coarse: boolean, default True
Determine whether to do a coarse or full experiment.
+
+
+
-
predict_labels(label_names)[source]¶
@@ -443,7 +485,10 @@
-
segmentations_from_this_directory(directory, segmentation_file_name='segmentation.nii.gz', glob='*/', is_training=True)[source]¶
Use segmentations from a directory as sources in WORC.
-SimpleWORC uses a directory glob to look for files meeting
+
Segmentations define the region of interest from which the features
+are extracted.
+
+SimpleWORC uses a directory glob to look for files meeting
the requirements to include, based on the input parameters.
Example:
When using “directory = C:UsersMyNameSegmentationFolder”,
@@ -453,11 +498,12 @@
- segmentation_file_name: string, default segmentation.nii.gz
Name of the files which will be included. Can include wildcards (*).
- glob: string, default */
Identify the search string to be used in the glob. Can include wildcards (*).
+- glob: string, default */
Identify the search string to be used in the glob. Can include wildcards (*).
- is_training: Boolean, default True
Identify whether these segmentations should be used in the training or test dataset.
diff --git a/WORC/doc/_build/html/autogen/WORC.featureprocessing.html b/WORC/doc/_build/html/autogen/WORC.featureprocessing.html
index 404e1ab5..592f20f6 100644
--- a/WORC/doc/_build/html/autogen/WORC.featureprocessing.html
+++ b/WORC/doc/_build/html/autogen/WORC.featureprocessing.html
@@ -8,7 +8,7 @@
- featureprocessing Package — WORC 3.4.2 documentation
+ featureprocessing Package — WORC 3.4.3 documentation
@@ -64,7 +64,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/autogen/WORC.html b/WORC/doc/_build/html/autogen/WORC.html
index a87276c0..9a2a9060 100644
--- a/WORC/doc/_build/html/autogen/WORC.html
+++ b/WORC/doc/_build/html/autogen/WORC.html
@@ -8,7 +8,7 @@
- WORC Package — WORC 3.4.2 documentation
+ WORC Package — WORC 3.4.3 documentation
@@ -64,7 +64,7 @@
- 3.4.2
+ 3.4.3
@@ -339,7 +339,7 @@
-
-
add_evaluation(label_type, modus='classification')[source]¶
+add_evaluation(label_type, modus='binary_classification')[source]¶
Add branch for evaluation of performance to network.
Note: should be done after build, before set:
WORC.build()
@@ -665,6 +665,7 @@
Subpackagestests Package
+WORCTutorialSimple_travis_multiclass ModuleWORCTutorialSimple_travis_regression Moduletest_combat Moduletest_helpers Moduleplotting Package — WORC 3.4.2 documentation
+ plotting Package — WORC 3.4.3 documentation
@@ -64,7 +64,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/autogen/WORC.processing.html b/WORC/doc/_build/html/autogen/WORC.processing.html
index 999e8cf0..88b112f8 100644
--- a/WORC/doc/_build/html/autogen/WORC.processing.html
+++ b/WORC/doc/_build/html/autogen/WORC.processing.html
@@ -8,7 +8,7 @@
- processing Package — WORC 3.4.2 documentation
+ processing Package — WORC 3.4.3 documentation
@@ -64,7 +64,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/autogen/WORC.resources.fastr_tests.html b/WORC/doc/_build/html/autogen/WORC.resources.fastr_tests.html
index 4c38b3c1..0a4aa4ff 100644
--- a/WORC/doc/_build/html/autogen/WORC.resources.fastr_tests.html
+++ b/WORC/doc/_build/html/autogen/WORC.resources.fastr_tests.html
@@ -8,7 +8,7 @@
- fastr_tests Package — WORC 3.4.2 documentation
+ fastr_tests Package — WORC 3.4.3 documentation
@@ -64,7 +64,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/autogen/WORC.resources.fastr_tools.html b/WORC/doc/_build/html/autogen/WORC.resources.fastr_tools.html
index 1a808e7d..45830455 100644
--- a/WORC/doc/_build/html/autogen/WORC.resources.fastr_tools.html
+++ b/WORC/doc/_build/html/autogen/WORC.resources.fastr_tools.html
@@ -8,7 +8,7 @@
- fastr_tools Package — WORC 3.4.2 documentation
+ fastr_tools Package — WORC 3.4.3 documentation
@@ -64,7 +64,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/autogen/WORC.resources.html b/WORC/doc/_build/html/autogen/WORC.resources.html
index 9bc82e18..ea40d83e 100644
--- a/WORC/doc/_build/html/autogen/WORC.resources.html
+++ b/WORC/doc/_build/html/autogen/WORC.resources.html
@@ -8,7 +8,7 @@
- resources Package — WORC 3.4.2 documentation
+ resources Package — WORC 3.4.3 documentation
@@ -64,7 +64,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/autogen/WORC.tools.html b/WORC/doc/_build/html/autogen/WORC.tools.html
index 3d286739..6c1029b4 100644
--- a/WORC/doc/_build/html/autogen/WORC.tools.html
+++ b/WORC/doc/_build/html/autogen/WORC.tools.html
@@ -8,7 +8,7 @@
- tools Package — WORC 3.4.2 documentation
+ tools Package — WORC 3.4.3 documentation
@@ -64,7 +64,7 @@
- 3.4.2
+ 3.4.3
@@ -262,7 +262,7 @@ tools Package
Evaluate Module¶
-
-class
WORC.tools.Evaluate.Evaluate(label_type, modus='classification', ensemble=50, scores='percentages', parent=None, features=None, fastr_plugin='LinearExecution', name='Example')[source]¶
+class WORC.tools.Evaluate.Evaluate(label_type, modus='binary_classification', ensemble=50, scores='percentages', parent=None, features=None, fastr_plugin='LinearExecution', name='Example')[source]¶
Bases: object
Build a network that evaluates the performance of an estimator.
@@ -272,7 +272,7 @@ tools Package
-
-
__init__(label_type, modus='classification', ensemble=50, scores='percentages', parent=None, features=None, fastr_plugin='LinearExecution', name='Example')[source]¶
+__init__(label_type, modus='binary_classification', ensemble=50, scores='percentages', parent=None, features=None, fastr_plugin='LinearExecution', name='Example')[source]¶
Initialize object.
- network: fastr network, default None
If you input a network, the evaluate network is added
diff --git a/WORC/doc/_build/html/genindex.html b/WORC/doc/_build/html/genindex.html
index 1555a998..deb51e58 100644
--- a/WORC/doc/_build/html/genindex.html
+++ b/WORC/doc/_build/html/genindex.html
@@ -9,7 +9,7 @@
-
Index — WORC 3.4.2 documentation
+ Index — WORC 3.4.3 documentation
@@ -63,7 +63,7 @@
- 3.4.2
+ 3.4.3
@@ -342,6 +342,8 @@ _
- (WORC.facade.helpers.exceptions.NoFeaturesFoundException method)
- (WORC.facade.helpers.exceptions.NoImagesFoundException method)
+
+ - (WORC.facade.helpers.exceptions.NoMasksFoundException method)
- (WORC.facade.helpers.exceptions.NoSegmentationsFoundException method)
@@ -468,6 +470,8 @@ _
- (WORC.facade.helpers.exceptions.NoFeaturesFoundException attribute)
- (WORC.facade.helpers.exceptions.NoImagesFoundException attribute)
+
+ - (WORC.facade.helpers.exceptions.NoMasksFoundException attribute)
- (WORC.facade.helpers.exceptions.NoSegmentationsFoundException attribute)
@@ -560,6 +564,8 @@ _
- (WORC.facade.helpers.exceptions.NoFeaturesFoundException attribute)
- (WORC.facade.helpers.exceptions.NoImagesFoundException attribute)
+
+ - (WORC.facade.helpers.exceptions.NoMasksFoundException attribute)
- (WORC.facade.helpers.exceptions.NoSegmentationsFoundException attribute)
@@ -1084,6 +1090,8 @@ M
- (in module WORC.resources.fastr_tests.elastix_test)
- (in module WORC.resources.fastr_tests.segmentix_test)
+
+ - (in module WORC.tests.WORCTutorialSimple_travis_multiclass)
- (in module WORC.tests.WORCTutorialSimple_travis_regression)
@@ -1095,6 +1103,8 @@ M
- manhattan_importance() (in module WORC.plotting.plot_pvalues_features)
- mask_contour() (in module WORC.processing.segmentix)
+
+ - masks_from_this_directory() (WORC.facade.simpleworc.SimpleWORC method)
- match() (WORC.processing.classes.switch method)
@@ -1105,6 +1115,8 @@ M
- multi_class_auc_score() (in module WORC.classification.metrics)
- multi_class_relief() (WORC.featureprocessing.Relief.SelectMulticlassRelief method)
+
+ - multiclass_classification() (WORC.facade.simpleworc.SimpleWORC method)
@@ -1121,6 +1133,8 @@ N
- NoImagesFoundException
+
+ - NoMasksFoundException
- normalize_image() (in module WORC.processing.preprocessing)
@@ -1597,6 +1611,8 @@ W
- WORC.tests.test_plot_errors (module)
- WORC.tests.test_validators (module)
+
+ - WORC.tests.WORCTutorialSimple_travis_multiclass (module)
- WORC.tests.WORCTutorialSimple_travis_regression (module)
diff --git a/WORC/doc/_build/html/index.html b/WORC/doc/_build/html/index.html
index 12ed2621..fec192a9 100644
--- a/WORC/doc/_build/html/index.html
+++ b/WORC/doc/_build/html/index.html
@@ -8,7 +8,7 @@
- WORC: Workflow for Optimal Radiomics Classification — WORC 3.4.2 documentation
+ WORC: Workflow for Optimal Radiomics Classification — WORC 3.4.3 documentation
@@ -63,7 +63,7 @@
- 3.4.2
+ 3.4.3
@@ -361,140 +361,145 @@ WORC DocumentationResource File Formats
- Changelog
-- 3.4.2 - Unreleased
+- 3.4.3 - 2021-06-02
-- 3.4.1 - 2021-05-18
-- Fixed
-- Changed
-- Added
+- 3.4.2 - 2021-05-27
-- 3.4.0 - 2021-02-02
-- Fixed
-- Changed
+- 3.4.1 - 2021-05-18
-- 3.3.5 - 2020-10-21
+- 3.4.0 - 2021-02-02
-- 3.3.4 - 2020-10-06
+- 3.3.5 - 2020-10-21
-- 3.3.3 - 2020-09-11
+- 3.3.4 - 2020-10-06
-- 3.3.2 - 2020-08-19
-- Fixed
-- Added
-- Changed
+- 3.3.3 - 2020-09-11
-- 3.3.1 - 2020-07-31
-- Changed
-- Fixed
+- 3.3.2 - 2020-08-19
-- 3.3.0 - 2020-07-28
-- Added
+- 3.3.1 - 2020-07-31
-- 3.2.2 - 2020-07-14
+- 3.3.0 - 2020-07-28
-- 3.2.1 - 2020-07-02
+- 3.2.2 - 2020-07-14
-- 3.2.0 - 2020-06-26
+- 3.2.1 - 2020-07-02
-- 3.1.4 - 2020-05-26
+- 3.2.0 - 2020-06-26
-- 3.1.3 - 2020-01-24
+- 3.1.4 - 2020-05-26
-- 3.1.2 - 2019-12-09
+- 3.1.3 - 2020-01-24
-- 3.1.1 - 2019-11-28
+- 3.1.2 - 2019-12-09
-- 3.1.0 - 2019-10-16
+- 3.1.1 - 2019-11-28
-- 3.0.0 - 2019-05-08
+- 3.1.0 - 2019-10-16
-- 2.1.3 - 2019-04-08
-- Changed
+- 3.0.0 - 2019-05-08
-- 2.1.2 - 2019-04-02
-- Added
-- Changed
-- Fixed
+- 2.1.3 - 2019-04-08
-- 2.1.1 - 2019-02-15
+- 2.1.2 - 2019-04-02
-- 2.1.0 - 2018-08-09
+- 2.1.1 - 2019-02-15
-- 2.0.0 - 2018-02-13
@@ -616,6 +621,7 @@ WORC Developer Module referencetests Package
+WORCTutorialSimple_travis_multiclass ModuleWORCTutorialSimple_travis_regression Moduletest_combat Moduletest_helpers ModulePython Module Index — WORC 3.4.2 documentation
+ Python Module Index — WORC 3.4.3 documentation
@@ -65,7 +65,7 @@
- 3.4.2
+ 3.4.3
@@ -570,6 +570,11 @@ Python Module Index
WORC.tests.test_validators
+
+
+ WORC.tests.WORCTutorialSimple_travis_multiclass
+
diff --git a/WORC/doc/_build/html/search.html b/WORC/doc/_build/html/search.html
index 68592fd4..f71ad058 100644
--- a/WORC/doc/_build/html/search.html
+++ b/WORC/doc/_build/html/search.html
@@ -8,7 +8,7 @@
- Search — WORC 3.4.2 documentation
+ Search — WORC 3.4.3 documentation
@@ -63,7 +63,7 @@
- 3.4.2
+ 3.4.3
diff --git a/WORC/doc/_build/html/searchindex.js b/WORC/doc/_build/html/searchindex.js
index e2364eb8..74d0c890 100644
--- a/WORC/doc/_build/html/searchindex.js
+++ b/WORC/doc/_build/html/searchindex.js
@@ -1 +1 @@
-Search.setIndex({docnames:["autogen/WORC","autogen/WORC.IOparser","autogen/WORC.classification","autogen/WORC.config","autogen/WORC.detectors","autogen/WORC.exampledata","autogen/WORC.facade","autogen/WORC.facade.helpers","autogen/WORC.fastrconfig","autogen/WORC.featureprocessing","autogen/WORC.plotting","autogen/WORC.processing","autogen/WORC.resources","autogen/WORC.resources.fastr_tests","autogen/WORC.resources.fastr_tools","autogen/WORC.statistics","autogen/WORC.tests","autogen/WORC.tools","autogen/WORC.validators","autogen/config/WORC.config_Bootstrap_defopts","autogen/config/WORC.config_Bootstrap_description","autogen/config/WORC.config_Classification_defopts","autogen/config/WORC.config_Classification_description","autogen/config/WORC.config_ComBat_defopts","autogen/config/WORC.config_ComBat_description","autogen/config/WORC.config_CrossValidation_defopts","autogen/config/WORC.config_CrossValidation_description","autogen/config/WORC.config_Ensemble_defopts","autogen/config/WORC.config_Ensemble_description","autogen/config/WORC.config_Evaluation_defopts","autogen/config/WORC.config_Evaluation_description","autogen/config/WORC.config_FeatPreProcess_defopts","autogen/config/WORC.config_FeatPreProcess_description","autogen/config/WORC.config_Featsel_defopts","autogen/config/WORC.config_Featsel_description","autogen/config/WORC.config_FeatureScaling_defopts","autogen/config/WORC.config_FeatureScaling_description","autogen/config/WORC.config_General_defopts","autogen/config/WORC.config_General_description","autogen/config/WORC.config_HyperOptimization_defopts","autogen/config/WORC.config_HyperOptimization_description","autogen/config/WORC.config_ImageFeatures_defopts","autogen/config/WORC.config_ImageFeatures_description","autogen/config/WORC.config_Imputation_defopts","autogen/config/WORC.config_Imputation_description","autogen/config/WORC.config_Labels_defopts","autogen/config/WORC.config_Labels_description","autogen/config/WORC.config_OneHotEncoding_defopts","autogen/config/WORC.config_OneHotEncoding_description","autogen/config/WORC.config_Preprocessing_defopts","autogen/config/WORC.config_Preprocessing_description","autogen/config/WORC.config_PyRadiomics_defopts","autogen/config/WORC.config_PyRadiomics_description","autogen/config/WORC.config_Resampling_defopts","autogen/config/WORC.config_Resampling_description","autogen/config/WORC.config_Segmentix_defopts","autogen/config/WORC.config_Segmentix_description","autogen/config/WORC.config_SelectFeatGroup_defopts","autogen/config/WORC.config_SelectFeatGroup_description","index","static/additionalfunctionality","static/changelog","static/configuration","static/datamining","static/developerdocumentation","static/faq","static/features","static/file_description","static/introduction","static/quick_start","static/user_manual"],envversion:{"sphinx.domains.c":1,"sphinx.domains.changeset":1,"sphinx.domains.cpp":1,"sphinx.domains.javascript":1,"sphinx.domains.math":2,"sphinx.domains.python":1,"sphinx.domains.rst":1,"sphinx.domains.std":1,"sphinx.ext.intersphinx":1,"sphinx.ext.todo":1,"sphinx.ext.viewcode":1,sphinx:56},filenames:["autogen/WORC.rst","autogen/WORC.IOparser.rst","autogen/WORC.classification.rst","autogen/WORC.config.rst","autogen/WORC.detectors.rst","autogen/WORC.exampledata.rst","autogen/WORC.facade.rst","autogen/WORC.facade.helpers.rst","autogen/WORC.fastrconfig.rst","autogen/WORC.featureprocessing.rst","autogen/WORC.plotting.rst","autogen/WORC.processing.rst","autogen/WORC.resources.rst","autogen/WORC.resources.fastr_tests.rst","autogen/WORC.resources.fastr_tools.rst","autogen/WORC.statistics.rst","autogen/WORC.tests.rst","autogen/WORC.tools.rst","autogen/WORC.validators.rst","autogen/config/WORC.config_Bootstrap_defopts.rst","autogen/config/WORC.config_Bootstrap_description.rst","autogen/config/WORC.config_Classification_defopts.rst","autogen/config/WORC.config_Classification_description.rst","autogen/config/WORC.config_ComBat_defopts.rst","autogen/config/WORC.config_ComBat_description.rst","autogen/config/WORC.config_CrossValidation_defopts.rst","autogen/config/WORC.config_CrossValidation_description.rst","autogen/config/WORC.config_Ensemble_defopts.rst","autogen/config/WORC.config_Ensemble_description.rst","autogen/config/WORC.config_Evaluation_defopts.rst","autogen/config/WORC.config_Evaluation_description.rst","autogen/config/WORC.config_FeatPreProcess_defopts.rst","autogen/config/WORC.config_FeatPreProcess_description.rst","autogen/config/WORC.config_Featsel_defopts.rst","autogen/config/WORC.config_Featsel_description.rst","autogen/config/WORC.config_FeatureScaling_defopts.rst","autogen/config/WORC.config_FeatureScaling_description.rst","autogen/config/WORC.config_General_defopts.rst","autogen/config/WORC.config_General_description.rst","autogen/config/WORC.config_HyperOptimization_defopts.rst","autogen/config/WORC.config_HyperOptimization_description.rst","autogen/config/WORC.config_ImageFeatures_defopts.rst","autogen/config/WORC.config_ImageFeatures_description.rst","autogen/config/WORC.config_Imputation_defopts.rst","autogen/config/WORC.config_Imputation_description.rst","autogen/config/WORC.config_Labels_defopts.rst","autogen/config/WORC.config_Labels_description.rst","autogen/config/WORC.config_OneHotEncoding_defopts.rst","autogen/config/WORC.config_OneHotEncoding_description.rst","autogen/config/WORC.config_Preprocessing_defopts.rst","autogen/config/WORC.config_Preprocessing_description.rst","autogen/config/WORC.config_PyRadiomics_defopts.rst","autogen/config/WORC.config_PyRadiomics_description.rst","autogen/config/WORC.config_Resampling_defopts.rst","autogen/config/WORC.config_Resampling_description.rst","autogen/config/WORC.config_Segmentix_defopts.rst","autogen/config/WORC.config_Segmentix_description.rst","autogen/config/WORC.config_SelectFeatGroup_defopts.rst","autogen/config/WORC.config_SelectFeatGroup_description.rst","index.rst","static/additionalfunctionality.rst","static/changelog.rst","static/configuration.rst","static/datamining.rst","static/developerdocumentation.rst","static/faq.rst","static/features.rst","static/file_description.rst","static/introduction.rst","static/quick_start.rst","static/user_manual.rst"],objects:{"WORC.IOparser":{config_WORC:[1,0,0,"-"],config_io_PyRadiomics:[1,0,0,"-"],config_io_classifier:[1,0,0,"-"],config_io_combat:[1,0,0,"-"],config_preprocessing:[1,0,0,"-"],config_segmentix:[1,0,0,"-"],file_io:[1,0,0,"-"]},"WORC.IOparser.config_WORC":{load_config:[1,1,1,""]},"WORC.IOparser.config_io_PyRadiomics":{load_config:[1,1,1,""]},"WORC.IOparser.config_io_classifier":{load_config:[1,1,1,""]},"WORC.IOparser.config_io_combat":{load_config:[1,1,1,""]},"WORC.IOparser.config_preprocessing":{load_config:[1,1,1,""]},"WORC.IOparser.config_segmentix":{load_config:[1,1,1,""]},"WORC.IOparser.file_io":{convert_config_pyradiomics:[1,1,1,""],load_data:[1,1,1,""],load_features:[1,1,1,""]},"WORC.WORC":{Tools:[0,2,1,""],WORC:[0,2,1,""]},"WORC.WORC.Tools":{__dict__:[0,3,1,""],__init__:[0,4,1,""],__module__:[0,3,1,""],__weakref__:[0,3,1,""]},"WORC.WORC.WORC":{__dict__:[0,3,1,""],__init__:[0,4,1,""],__module__:[0,3,1,""],__weakref__:[0,3,1,""],add_ComBat:[0,4,1,""],add_elastix:[0,4,1,""],add_elastix_sourcesandsinks:[0,4,1,""],add_evaluation:[0,4,1,""],add_feature_calculator:[0,4,1,""],add_preprocessing:[0,4,1,""],add_segmentix:[0,4,1,""],add_tools:[0,4,1,""],build:[0,4,1,""],build_training:[0,4,1,""],defaultconfig:[0,4,1,""],execute:[0,4,1,""],save_config:[0,4,1,""],set:[0,4,1,""]},"WORC.addexceptions":{WORCAssertionError:[0,5,1,""],WORCError:[0,5,1,""],WORCIOError:[0,5,1,""],WORCIndexError:[0,5,1,""],WORCKeyError:[0,5,1,""],WORCNotImplementedError:[0,5,1,""],WORCTypeError:[0,5,1,""],WORCValueError:[0,5,1,""]},"WORC.addexceptions.WORCAssertionError":{__module__:[0,3,1,""]},"WORC.addexceptions.WORCError":{__module__:[0,3,1,""],__weakref__:[0,3,1,""]},"WORC.addexceptions.WORCIOError":{__module__:[0,3,1,""],__weakref__:[0,3,1,""]},"WORC.addexceptions.WORCIndexError":{__module__:[0,3,1,""]},"WORC.addexceptions.WORCKeyError":{__module__:[0,3,1,""]},"WORC.addexceptions.WORCNotImplementedError":{__module__:[0,3,1,""]},"WORC.addexceptions.WORCTypeError":{__module__:[0,3,1,""]},"WORC.addexceptions.WORCValueError":{__module__:[0,3,1,""]},"WORC.classification":{AdvancedSampler:[2,0,0,"-"],ObjectSampler:[2,0,0,"-"],RankedSVM:[2,0,0,"-"],SearchCV:[2,0,0,"-"],construct_classifier:[2,0,0,"-"],createfixedsplits:[2,0,0,"-"],crossval:[2,0,0,"-"],estimators:[2,0,0,"-"],fitandscore:[2,0,0,"-"],metrics:[2,0,0,"-"],parameter_optimization:[2,0,0,"-"],regressors:[2,0,0,"-"],trainclassifier:[2,0,0,"-"]},"WORC.classification.AdvancedSampler":{AdvancedSampler:[2,2,1,""],boolean_uniform:[2,2,1,""],discrete_uniform:[2,2,1,""],exp_uniform:[2,2,1,""],log_uniform:[2,2,1,""]},"WORC.classification.AdvancedSampler.AdvancedSampler":{__dict__:[2,3,1,""],__init__:[2,4,1,""],__iter__:[2,4,1,""],__len__:[2,4,1,""],__module__:[2,3,1,""],__weakref__:[2,3,1,""]},"WORC.classification.AdvancedSampler.boolean_uniform":{__dict__:[2,3,1,""],__init__:[2,4,1,""],__module__:[2,3,1,""],__weakref__:[2,3,1,""],rvs:[2,4,1,""]},"WORC.classification.AdvancedSampler.discrete_uniform":{__dict__:[2,3,1,""],__init__:[2,4,1,""],__module__:[2,3,1,""],__weakref__:[2,3,1,""],rvs:[2,4,1,""]},"WORC.classification.AdvancedSampler.exp_uniform":{__dict__:[2,3,1,""],__init__:[2,4,1,""],__module__:[2,3,1,""],__weakref__:[2,3,1,""],rvs:[2,4,1,""]},"WORC.classification.AdvancedSampler.log_uniform":{__dict__:[2,3,1,""],__init__:[2,4,1,""],__module__:[2,3,1,""],__weakref__:[2,3,1,""],rvs:[2,4,1,""]},"WORC.classification.ObjectSampler":{ObjectSampler:[2,2,1,""]},"WORC.classification.ObjectSampler.ObjectSampler":{__dict__:[2,3,1,""],__init__:[2,4,1,""],__module__:[2,3,1,""],__weakref__:[2,3,1,""],fit:[2,4,1,""],init_ADASYN:[2,4,1,""],init_BorderlineSMOTE:[2,4,1,""],init_NearMiss:[2,4,1,""],init_NeighbourhoodCleaningRule:[2,4,1,""],init_RandomOverSampling:[2,4,1,""],init_RandomUnderSampling:[2,4,1,""],init_SMOTE:[2,4,1,""],init_SMOTEENN:[2,4,1,""],init_SMOTETomek:[2,4,1,""],transform:[2,4,1,""]},"WORC.classification.RankedSVM":{RankSVM_test:[2,1,1,""],RankSVM_test_original:[2,1,1,""],RankSVM_train:[2,1,1,""],RankSVM_train_old:[2,1,1,""],is_empty:[2,1,1,""],neg_dual_func:[2,1,1,""]},"WORC.classification.SearchCV":{BaseSearchCV:[2,2,1,""],BaseSearchCVJoblib:[2,2,1,""],BaseSearchCVfastr:[2,2,1,""],Ensemble:[2,2,1,""],GridSearchCVJoblib:[2,2,1,""],GridSearchCVfastr:[2,2,1,""],RandomizedSearchCVJoblib:[2,2,1,""],RandomizedSearchCVfastr:[2,2,1,""],chunks:[2,1,1,""],chunksdict:[2,1,1,""],rms_score:[2,1,1,""],sar_score:[2,1,1,""]},"WORC.classification.SearchCV.BaseSearchCV":{__abstractmethods__:[2,3,1,""],__init__:[2,4,1,""],__module__:[2,3,1,""],create_ensemble:[2,4,1,""],decision_function:[2,4,1,""],inverse_transform:[2,4,1,""],predict:[2,4,1,""],predict_log_proba:[2,4,1,""],predict_proba:[2,4,1,""],preprocess:[2,4,1,""],process_fit:[2,4,1,""],refit_and_score:[2,4,1,""],score:[2,4,1,""],transform:[2,4,1,""]},"WORC.classification.SearchCV.BaseSearchCVJoblib":{__abstractmethods__:[2,3,1,""],__module__:[2,3,1,""]},"WORC.classification.SearchCV.BaseSearchCVfastr":{__abstractmethods__:[2,3,1,""],__module__:[2,3,1,""]},"WORC.classification.SearchCV.Ensemble":{__abstractmethods__:[2,3,1,""],__init__:[2,4,1,""],__module__:[2,3,1,""],decision_function:[2,4,1,""],inverse_transform:[2,4,1,""],predict:[2,4,1,""],predict_log_proba:[2,4,1,""],predict_proba:[2,4,1,""],transform:[2,4,1,""]},"WORC.classification.SearchCV.GridSearchCVJoblib":{__abstractmethods__:[2,3,1,""],__init__:[2,4,1,""],__module__:[2,3,1,""],fit:[2,4,1,""]},"WORC.classification.SearchCV.GridSearchCVfastr":{__abstractmethods__:[2,3,1,""],__init__:[2,4,1,""],__module__:[2,3,1,""],fit:[2,4,1,""]},"WORC.classification.SearchCV.RandomizedSearchCVJoblib":{__abstractmethods__:[2,3,1,""],__init__:[2,4,1,""],__module__:[2,3,1,""],fit:[2,4,1,""]},"WORC.classification.SearchCV.RandomizedSearchCVfastr":{__abstractmethods__:[2,3,1,""],__init__:[2,4,1,""],__module__:[2,3,1,""],fit:[2,4,1,""]},"WORC.classification.construct_classifier":{construct_SVM:[2,1,1,""],construct_classifier:[2,1,1,""],create_param_grid:[2,1,1,""]},"WORC.classification.createfixedsplits":{createfixedsplits:[2,1,1,""]},"WORC.classification.crossval":{LOO_cross_validation:[2,1,1,""],crossval:[2,1,1,""],nocrossval:[2,1,1,""],random_split_cross_validation:[2,1,1,""],test_RS_Ensemble:[2,1,1,""]},"WORC.classification.estimators":{RankedSVM:[2,2,1,""]},"WORC.classification.estimators.RankedSVM":{__init__:[2,4,1,""],__module__:[2,3,1,""],fit:[2,4,1,""],predict:[2,4,1,""],predict_proba:[2,4,1,""]},"WORC.classification.fitandscore":{delete_cc_para:[2,1,1,""],delete_nonestimator_parameters:[2,1,1,""],fit_and_score:[2,1,1,""],replacenan:[2,1,1,""]},"WORC.classification.metrics":{ICC:[2,1,1,""],ICC_anova:[2,1,1,""],check_multimetric_scoring:[2,1,1,""],check_scoring:[2,1,1,""],f1_weighted_predictproba:[2,1,1,""],multi_class_auc:[2,1,1,""],multi_class_auc_score:[2,1,1,""],pairwise_auc:[2,1,1,""],performance_multilabel:[2,1,1,""],performance_singlelabel:[2,1,1,""]},"WORC.classification.parameter_optimization":{random_search_parameters:[2,1,1,""]},"WORC.classification.trainclassifier":{add_parameters_to_grid:[2,1,1,""],trainclassifier:[2,1,1,""]},"WORC.detectors":{detectors:[4,0,0,"-"]},"WORC.detectors.detectors":{AbstractDetector:[4,2,1,""],BigrClusterDetector:[4,2,1,""],CartesiusClusterDetector:[4,2,1,""],CsvDetector:[4,2,1,""],DebugDetector:[4,2,1,""],HostnameDetector:[4,2,1,""],LinuxDetector:[4,2,1,""],WORCDirectoryDetector:[4,2,1,""]},"WORC.detectors.detectors.AbstractDetector":{__abstractmethods__:[4,3,1,""],__dict__:[4,3,1,""],__module__:[4,3,1,""],__weakref__:[4,3,1,""],do_detection:[4,4,1,""]},"WORC.detectors.detectors.BigrClusterDetector":{__abstractmethods__:[4,3,1,""],__module__:[4,3,1,""]},"WORC.detectors.detectors.CartesiusClusterDetector":{__abstractmethods__:[4,3,1,""],__module__:[4,3,1,""]},"WORC.detectors.detectors.CsvDetector":{__abstractmethods__:[4,3,1,""],__init__:[4,4,1,""],__module__:[4,3,1,""]},"WORC.detectors.detectors.DebugDetector":{__abstractmethods__:[4,3,1,""],__module__:[4,3,1,""]},"WORC.detectors.detectors.HostnameDetector":{__abstractmethods__:[4,3,1,""],__init__:[4,4,1,""],__module__:[4,3,1,""]},"WORC.detectors.detectors.LinuxDetector":{__abstractmethods__:[4,3,1,""],__module__:[4,3,1,""]},"WORC.detectors.detectors.WORCDirectoryDetector":{__abstractmethods__:[4,3,1,""],__module__:[4,3,1,""]},"WORC.exampledata":{create_example_data:[5,0,0,"-"],datadownloader:[5,0,0,"-"]},"WORC.exampledata.create_example_data":{create_random_features:[5,1,1,""]},"WORC.exampledata.datadownloader":{download_HeadAndNeck:[5,1,1,""],download_project:[5,1,1,""],download_subject:[5,1,1,""]},"WORC.facade":{basicworc:[6,0,0,"-"],simpleworc:[6,0,0,"-"]},"WORC.facade.basicworc":{BasicWORC:[6,2,1,""]},"WORC.facade.basicworc.BasicWORC":{__init__:[6,4,1,""],__module__:[6,3,1,""],execute:[6,4,1,""]},"WORC.facade.helpers":{configbuilder:[7,0,0,"-"],exceptions:[7,0,0,"-"],processing:[7,0,0,"-"]},"WORC.facade.helpers.configbuilder":{ConfigBuilder:[7,2,1,""]},"WORC.facade.helpers.configbuilder.ConfigBuilder":{__dict__:[7,3,1,""],__init__:[7,4,1,""],__module__:[7,3,1,""],__weakref__:[7,3,1,""],build_config:[7,4,1,""],coarse_overrides:[7,4,1,""],custom_config_overrides:[7,4,1,""],estimator_scoring_overrides:[7,4,1,""],fullprint:[7,4,1,""]},"WORC.facade.helpers.exceptions":{InvalidCsvFileException:[7,5,1,""],InvalidOrderException:[7,5,1,""],NoFeaturesFoundException:[7,5,1,""],NoImagesFoundException:[7,5,1,""],NoSegmentationsFoundException:[7,5,1,""],PathNotFoundException:[7,5,1,""]},"WORC.facade.helpers.exceptions.InvalidCsvFileException":{__init__:[7,4,1,""],__module__:[7,3,1,""],__weakref__:[7,3,1,""]},"WORC.facade.helpers.exceptions.InvalidOrderException":{__init__:[7,4,1,""],__module__:[7,3,1,""],__weakref__:[7,3,1,""]},"WORC.facade.helpers.exceptions.NoFeaturesFoundException":{__init__:[7,4,1,""],__module__:[7,3,1,""],__weakref__:[7,3,1,""]},"WORC.facade.helpers.exceptions.NoImagesFoundException":{__init__:[7,4,1,""],__module__:[7,3,1,""],__weakref__:[7,3,1,""]},"WORC.facade.helpers.exceptions.NoSegmentationsFoundException":{__init__:[7,4,1,""],__module__:[7,3,1,""],__weakref__:[7,3,1,""]},"WORC.facade.helpers.exceptions.PathNotFoundException":{__init__:[7,4,1,""],__module__:[7,3,1,""],__weakref__:[7,3,1,""]},"WORC.facade.helpers.processing":{convert_radiomix_features:[7,1,1,""]},"WORC.facade.simpleworc":{SimpleWORC:[6,2,1,""]},"WORC.facade.simpleworc.SimpleWORC":{__dict__:[6,3,1,""],__init__:[6,4,1,""],__module__:[6,3,1,""],__weakref__:[6,3,1,""],add_config_overrides:[6,4,1,""],add_evaluation:[6,4,1,""],binary_classification:[6,4,1,""],count_num_subjects:[6,4,1,""],execute:[6,4,1,""],features_from_radiomix_xlsx:[6,4,1,""],features_from_this_directory:[6,4,1,""],images_from_this_directory:[6,4,1,""],labels_from_this_file:[6,4,1,""],predict_labels:[6,4,1,""],regression:[6,4,1,""],segmentations_from_this_directory:[6,4,1,""],semantics_from_this_file:[6,4,1,""],set_fixed_splits:[6,4,1,""],set_multicore_execution:[6,4,1,""],set_tmpdir:[6,4,1,""],survival:[6,4,1,""]},"WORC.featureprocessing":{ComBat:[9,0,0,"-"],Decomposition:[9,0,0,"-"],FeatureConverter:[9,0,0,"-"],ICCThreshold:[9,0,0,"-"],Imputer:[9,0,0,"-"],OneHotEncoderWrapper:[9,0,0,"-"],Preprocessor:[9,0,0,"-"],Relief:[9,0,0,"-"],Scalers:[9,0,0,"-"],SelectGroups:[9,0,0,"-"],SelectIndividuals:[9,0,0,"-"],StatisticalTestFeatures:[9,0,0,"-"],StatisticalTestThreshold:[9,0,0,"-"],VarianceThreshold:[9,0,0,"-"]},"WORC.featureprocessing.ComBat":{ComBat:[9,1,1,""],ComBatMatlab:[9,1,1,""],ComBatPython:[9,1,1,""],Synthetictest:[9,1,1,""]},"WORC.featureprocessing.Decomposition":{Decomposition:[9,1,1,""]},"WORC.featureprocessing.FeatureConverter":{FeatureConverter:[9,1,1,""],convert_PREDICT:[9,1,1,""],convert_pyradiomics:[9,1,1,""],convert_pyradiomics_featurevector:[9,1,1,""]},"WORC.featureprocessing.ICCThreshold":{ICCThreshold:[9,2,1,""],convert_features_ICC_threshold:[9,1,1,""]},"WORC.featureprocessing.ICCThreshold.ICCThreshold":{__abstractmethods__:[9,3,1,""],__init__:[9,4,1,""],__module__:[9,3,1,""],fit:[9,4,1,""],transform:[9,4,1,""]},"WORC.featureprocessing.Imputer":{Imputer:[9,2,1,""]},"WORC.featureprocessing.Imputer.Imputer":{__dict__:[9,3,1,""],__init__:[9,4,1,""],__module__:[9,3,1,""],__weakref__:[9,3,1,""],fit:[9,4,1,""],transform:[9,4,1,""]},"WORC.featureprocessing.OneHotEncoderWrapper":{OneHotEncoderWrapper:[9,2,1,""],test:[9,1,1,""]},"WORC.featureprocessing.OneHotEncoderWrapper.OneHotEncoderWrapper":{__dict__:[9,3,1,""],__init__:[9,4,1,""],__module__:[9,3,1,""],__weakref__:[9,3,1,""],fit:[9,4,1,""],transform:[9,4,1,""]},"WORC.featureprocessing.Preprocessor":{Preprocessor:[9,2,1,""]},"WORC.featureprocessing.Preprocessor.Preprocessor":{__dict__:[9,3,1,""],__init__:[9,4,1,""],__module__:[9,3,1,""],__weakref__:[9,3,1,""],fit:[9,4,1,""],transform:[9,4,1,""]},"WORC.featureprocessing.Relief":{SelectMulticlassRelief:[9,2,1,""]},"WORC.featureprocessing.Relief.SelectMulticlassRelief":{__abstractmethods__:[9,3,1,""],__init__:[9,4,1,""],__module__:[9,3,1,""],fit:[9,4,1,""],multi_class_relief:[9,4,1,""],single_class_relief:[9,4,1,""],transform:[9,4,1,""]},"WORC.featureprocessing.Scalers":{LogStandardScaler:[9,2,1,""],RobustStandardScaler:[9,2,1,""],WORCScaler:[9,2,1,""],test:[9,1,1,""]},"WORC.featureprocessing.Scalers.LogStandardScaler":{__module__:[9,3,1,""],fit:[9,4,1,""]},"WORC.featureprocessing.Scalers.RobustStandardScaler":{__module__:[9,3,1,""],fit:[9,4,1,""]},"WORC.featureprocessing.Scalers.WORCScaler":{__init__:[9,4,1,""],__module__:[9,3,1,""],fit:[9,4,1,""],transform:[9,4,1,""]},"WORC.featureprocessing.SelectGroups":{SelectGroups:[9,2,1,""]},"WORC.featureprocessing.SelectGroups.SelectGroups":{__abstractmethods__:[9,3,1,""],__init__:[9,4,1,""],__module__:[9,3,1,""],fit:[9,4,1,""],transform:[9,4,1,""]},"WORC.featureprocessing.SelectIndividuals":{SelectIndividuals:[9,2,1,""]},"WORC.featureprocessing.SelectIndividuals.SelectIndividuals":{__abstractmethods__:[9,3,1,""],__init__:[9,4,1,""],__module__:[9,3,1,""],fit:[9,4,1,""],transform:[9,4,1,""]},"WORC.featureprocessing.StatisticalTestFeatures":{StatisticalTestFeatures:[9,1,1,""]},"WORC.featureprocessing.StatisticalTestThreshold":{StatisticalTestThreshold:[9,2,1,""]},"WORC.featureprocessing.StatisticalTestThreshold.StatisticalTestThreshold":{__abstractmethods__:[9,3,1,""],__init__:[9,4,1,""],__module__:[9,3,1,""],fit:[9,4,1,""],transform:[9,4,1,""]},"WORC.featureprocessing.VarianceThreshold":{VarianceThresholdMean:[9,2,1,""],selfeat_variance:[9,1,1,""]},"WORC.featureprocessing.VarianceThreshold.VarianceThresholdMean":{__abstractmethods__:[9,3,1,""],__init__:[9,4,1,""],__module__:[9,3,1,""],fit:[9,4,1,""],transform:[9,4,1,""]},"WORC.plotting":{compute_CI:[10,0,0,"-"],linstretch:[10,0,0,"-"],plot_ROC:[10,0,0,"-"],plot_barchart:[10,0,0,"-"],plot_boxplot_features:[10,0,0,"-"],plot_boxplot_performance:[10,0,0,"-"],plot_errors:[10,0,0,"-"],plot_estimator_performance:[10,0,0,"-"],plot_hyperparameters:[10,0,0,"-"],plot_images:[10,0,0,"-"],plot_pvalues_features:[10,0,0,"-"],plot_ranked_scores:[10,0,0,"-"],plotminmaxresponse:[10,0,0,"-"],scatterplot:[10,0,0,"-"]},"WORC.plotting.compute_CI":{compute_confidence:[10,1,1,""],compute_confidence_bootstrap:[10,1,1,""],compute_confidence_logit:[10,1,1,""]},"WORC.plotting.linstretch":{linstretch:[10,1,1,""]},"WORC.plotting.plot_ROC":{curve_thresholding:[10,1,1,""],main:[10,1,1,""],plot_PRC_CIc:[10,1,1,""],plot_ROC:[10,1,1,""],plot_ROC_CIc:[10,1,1,""],plot_single_PRC:[10,1,1,""],plot_single_ROC:[10,1,1,""]},"WORC.plotting.plot_barchart":{count_parameters:[10,1,1,""],main:[10,1,1,""],paracheck:[10,1,1,""],plot_barchart:[10,1,1,""],plot_bars:[10,1,1,""]},"WORC.plotting.plot_boxplot_features":{generate_feature_boxplots:[10,1,1,""],plot_boxplot_features:[10,1,1,""]},"WORC.plotting.plot_boxplot_performance":{generate_performance_boxplots:[10,1,1,""],test:[10,1,1,""]},"WORC.plotting.plot_errors":{plot_errors:[10,1,1,""]},"WORC.plotting.plot_estimator_performance":{combine_multiple_estimators:[10,1,1,""],compute_statistics:[10,1,1,""],fit_thresholds:[10,1,1,""],main:[10,1,1,""],plot_estimator_performance:[10,1,1,""]},"WORC.plotting.plot_hyperparameters":{plot_hyperparameters:[10,1,1,""]},"WORC.plotting.plot_images":{bbox_2D:[10,1,1,""],extract_boundary:[10,1,1,""],plot_im_and_overlay:[10,1,1,""],slicer:[10,1,1,""]},"WORC.plotting.plot_pvalues_features":{manhattan_importance:[10,1,1,""]},"WORC.plotting.plot_ranked_scores":{example:[10,1,1,""],flatten_object:[10,1,1,""],main:[10,1,1,""],plot_ranked_images:[10,1,1,""],plot_ranked_percentages:[10,1,1,""],plot_ranked_posteriors:[10,1,1,""],plot_ranked_scores:[10,1,1,""]},"WORC.plotting.plotminmaxresponse":{main:[10,1,1,""]},"WORC.plotting.scatterplot":{main:[10,1,1,""],make_scatterplot:[10,1,1,""]},"WORC.processing":{ExtractNLargestBlobsn:[11,0,0,"-"],classes:[11,0,0,"-"],helpers:[11,0,0,"-"],label_processing:[11,0,0,"-"],preprocessing:[11,0,0,"-"],segmentix:[11,0,0,"-"]},"WORC.processing.ExtractNLargestBlobsn":{ExtractNLargestBlobsn:[11,1,1,""]},"WORC.processing.classes":{"switch":[11,2,1,""]},"WORC.processing.classes.switch":{__dict__:[11,3,1,""],__init__:[11,4,1,""],__iter__:[11,4,1,""],__module__:[11,3,1,""],__weakref__:[11,3,1,""],match:[11,4,1,""]},"WORC.processing.helpers":{check_image_orientation:[11,1,1,""],resample_image:[11,1,1,""],transpose_image:[11,1,1,""]},"WORC.processing.label_processing":{findlabeldata:[11,1,1,""],load_config_XNAT:[11,1,1,""],load_label_XNAT:[11,1,1,""],load_label_csv:[11,1,1,""],load_label_txt:[11,1,1,""],load_labels:[11,1,1,""]},"WORC.processing.preprocessing":{bias_correct_image:[11,1,1,""],clip_image:[11,1,1,""],normalize_image:[11,1,1,""],preprocess:[11,1,1,""]},"WORC.processing.segmentix":{dilate_contour:[11,1,1,""],get_ring:[11,1,1,""],mask_contour:[11,1,1,""],segmentix:[11,1,1,""]},"WORC.resources":{fastr_tools:[14,0,0,"-"]},"WORC.resources.fastr_tests":{CalcFeatures_test:[13,0,0,"-"],elastix_test:[13,0,0,"-"],segmentix_test:[13,0,0,"-"]},"WORC.resources.fastr_tests.CalcFeatures_test":{create_network:[13,1,1,""],main:[13,1,1,""],sink_data:[13,1,1,""],source_data:[13,1,1,""]},"WORC.resources.fastr_tests.elastix_test":{create_network:[13,1,1,""],main:[13,1,1,""],sink_data:[13,1,1,""],source_data:[13,1,1,""]},"WORC.resources.fastr_tests.segmentix_test":{create_network:[13,1,1,""],main:[13,1,1,""],sink_data:[13,1,1,""],source_data:[13,1,1,""]},"WORC.statistics":{delong:[15,0,0,"-"]},"WORC.statistics.delong":{calc_pvalue:[15,1,1,""],compute_ground_truth_statistics:[15,1,1,""],compute_midrank:[15,1,1,""],compute_midrank_weight:[15,1,1,""],delong_roc_test:[15,1,1,""],delong_roc_variance:[15,1,1,""],fastDeLong:[15,1,1,""]},"WORC.tests":{WORCTutorialSimple_travis_regression:[16,0,0,"-"],test_combat:[16,0,0,"-"],test_helpers:[16,0,0,"-"],test_iccthreshold:[16,0,0,"-"],test_plot_errors:[16,0,0,"-"],test_validators:[16,0,0,"-"]},"WORC.tests.WORCTutorialSimple_travis_regression":{main:[16,1,1,""]},"WORC.tests.test_combat":{test_combat:[16,1,1,""],test_combat_fastr:[16,1,1,""]},"WORC.tests.test_helpers":{find_exampledatadir:[16,1,1,""],find_testdatadir:[16,1,1,""]},"WORC.tests.test_iccthreshold":{test_iccthreshold:[16,1,1,""]},"WORC.tests.test_plot_errors":{test_plot_errors:[16,1,1,""]},"WORC.tests.test_validators":{test_invalidlabelsvalidator_columnsubstring:[16,1,1,""],test_invalidlabelsvalidator_patientcolumn:[16,1,1,""],test_invalidlabelsvalidator_patientsubstring:[16,1,1,""],test_invalidlabelsvalidator_validconfig:[16,1,1,""]},"WORC.tools":{Elastix:[17,0,0,"-"],Evaluate:[17,0,0,"-"],Inference:[17,0,0,"-"],Slicer:[17,0,0,"-"],Transformix:[17,0,0,"-"],createfixedsplits:[17,0,0,"-"]},"WORC.tools.Elastix":{Elastix:[17,2,1,""]},"WORC.tools.Elastix.Elastix":{__dict__:[17,3,1,""],__init__:[17,4,1,""],__module__:[17,3,1,""],__weakref__:[17,3,1,""],addchangeorder:[17,4,1,""],create_bbox:[17,4,1,""],create_network:[17,4,1,""],execute:[17,4,1,""],getparametermap:[17,4,1,""]},"WORC.tools.Evaluate":{Evaluate:[17,2,1,""]},"WORC.tools.Evaluate.Evaluate":{__dict__:[17,3,1,""],__init__:[17,4,1,""],__module__:[17,3,1,""],__weakref__:[17,3,1,""],create_links_Addon:[17,4,1,""],create_links_Standalone:[17,4,1,""],create_network:[17,4,1,""],execute:[17,4,1,""],set:[17,4,1,""]},"WORC.tools.Inference":{Inference:[17,2,1,""]},"WORC.tools.Inference.Inference":{__dict__:[17,3,1,""],__init__:[17,4,1,""],__module__:[17,3,1,""],__weakref__:[17,3,1,""],create_network:[17,4,1,""]},"WORC.tools.Slicer":{Slicer:[17,2,1,""]},"WORC.tools.Slicer.Slicer":{__dict__:[17,3,1,""],__init__:[17,4,1,""],__module__:[17,3,1,""],__weakref__:[17,3,1,""],create_network:[17,4,1,""],execute:[17,4,1,""],set:[17,4,1,""]},"WORC.tools.Transformix":{Transformix:[17,2,1,""]},"WORC.tools.Transformix.Transformix":{__dict__:[17,3,1,""],__init__:[17,4,1,""],__module__:[17,3,1,""],__weakref__:[17,3,1,""],create_network:[17,4,1,""],execute:[17,4,1,""]},"WORC.tools.createfixedsplits":{createfixedsplits:[17,1,1,""]},"WORC.validators":{preflightcheck:[18,0,0,"-"]},"WORC.validators.preflightcheck":{AbstractValidator:[18,2,1,""],EvaluateValidator:[18,2,1,""],InvalidLabelsValidator:[18,2,1,""],MinSubjectsValidator:[18,2,1,""],SamplesWarning:[18,2,1,""],SimpleValidator:[18,2,1,""],ValidatorsFactory:[18,2,1,""]},"WORC.validators.preflightcheck.AbstractValidator":{__abstractmethods__:[18,3,1,""],__dict__:[18,3,1,""],__module__:[18,3,1,""],__weakref__:[18,3,1,""],do_validation:[18,4,1,""]},"WORC.validators.preflightcheck.EvaluateValidator":{__abstractmethods__:[18,3,1,""],__module__:[18,3,1,""]},"WORC.validators.preflightcheck.InvalidLabelsValidator":{__abstractmethods__:[18,3,1,""],__module__:[18,3,1,""]},"WORC.validators.preflightcheck.MinSubjectsValidator":{__abstractmethods__:[18,3,1,""],__module__:[18,3,1,""]},"WORC.validators.preflightcheck.SamplesWarning":{__abstractmethods__:[18,3,1,""],__module__:[18,3,1,""]},"WORC.validators.preflightcheck.SimpleValidator":{__abstractmethods__:[18,3,1,""],__module__:[18,3,1,""]},"WORC.validators.preflightcheck.ValidatorsFactory":{__dict__:[18,3,1,""],__module__:[18,3,1,""],__weakref__:[18,3,1,""],factor_validators:[18,6,1,""]},WORC:{WORC:[0,0,0,"-"],__init__:[0,0,0,"-"],addexceptions:[0,0,0,"-"],classification:[2,0,0,"-"],facade:[6,0,0,"-"],featureprocessing:[9,0,0,"-"],plotting:[10,0,0,"-"]}},objnames:{"0":["py","module","Python module"],"1":["py","function","Python function"],"2":["py","class","Python class"],"3":["py","attribute","Python attribute"],"4":["py","method","Python method"],"5":["py","exception","Python exception"],"6":["py","staticmethod","Python static method"]},objtypes:{"0":"py:module","1":"py:function","2":"py:class","3":"py:attribute","4":"py:method","5":"py:exception","6":"py:staticmethod"},terms:{"0284186x":9,"06875v1":9,"0a1":66,"0rc1":59,"105741d":59,"1st":2,"1x1x1":[50,60,62],"22nd":70,"2nd":[2,66],"5th":9,"95th":9,"95varianc":[33,34,62],"98nd":66,"boolean":[0,1,2,6,9,10,11,19,25,31,33,39,43,47,51,52,57,59,61,62],"case":[2,11,24,61,62,64,66,70],"catch":[0,61],"class":[0,2,4,6,7,9,15,17,18,59,61,64,70],"default":[0,1,2,6,9,10,11,17,19,21,22,23,25,27,28,29,31,33,35,37,39,41,43,45,47,49,51,53,55,57,60,61,62,64,65,66,69,70],"export":68,"final":[2,9,11,62,70],"float":[2,9,10,11,15,21,25,33,39,41,42,49,51,53,61,62,66],"function":[0,2,4,6,7,9,10,11,16,17,18,22,50,59,61,62,63,64,65,66,67,69,70],"gr\u00fcnhagen":59,"import":[2,9,34,59,61,62,68,70],"int":[2,9,11],"long":66,"new":[0,59,61,66,68],"return":[0,1,2,9,10,11,15,61,64],"short":66,"static":[18,42,62],"switch":[9,11,61],"throw":[61,66],"true":[0,2,5,6,9,10,11,21,26,29,32,33,37,38,40,41,43,44,48,49,50,51,55,57,58,60,62,69,70],"try":[2,60,68],"while":[2,11,40,61,62,66],Added:59,Adding:59,Age:69,And:9,Els:59,For:[0,2,6,9,22,42,48,59,60,61,62,63,64,65,66,68,69,70],IDs:[11,65],Not:[2,6,61,68],One:[2,54,61,62],PCs:[22,62],SVs:2,That:9,The:[0,1,2,6,9,10,11,15,26,34,46,59,60,61,62,63,64,65,66,67,68],Then:2,There:[61,69,70],These:[10,62,64,66,69,70],USING:59,Use:[2,6,19,20,22,27,28,31,32,47,48,53,54,61,62,66,69],Using:[59,68],Vos:59,Was:61,Will:6,With:59,__abstractmethods__:[2,4,9,18],__dict__:[0,2,4,6,7,9,11,17,18],__doc__:[0,2,4,6,7,9,11,17,18],__file__:69,__init__:[0,2,4,6,7,9,11,17],__iter__:[2,11],__len__:2,__module__:[0,2,4,6,7,9,11,17,18],__weakref__:[0,2,4,6,7,9,11,17,18],_abc_data:[4,18],_abc_impl:[4,18],_base:9,_cluster_config_overrid:7,_data:9,_debug_config_overrid:7,_format_result:2,_generate_detector_messag:[4,18],_is_detect:4,_set_and_validate_estim:6,_valid:[6,18],abbrevi:[22,62],abc:[4,18],about:66,abov:[2,9,60,61,62,66,68,69,70],absolut:61,abspath:69,abstractdetector:4,abstractvalid:18,accept:[2,39,61,62],accorad:2,accord:[2,9,10,66,69,70],accordingli:[60,69],account:[9,10,70],accur:[2,4,7,9,11,17],accuraci:[2,10,70],acquisit:68,across:2,act:62,actual:[0,2,6,30,59,60,61,62,63,64,68,70],adaboost:[22,61,62],adaboost_learning_r:[21,22,62],adaboost_n_estim:[21,22,62],adaboostclassifi:[21,62],adaboostregressor:[21,62],adapt:[59,68],adasyn:[2,53,61,62],add:[0,2,6,9,17,61,64,65,66,67,69,70],add_combat:0,add_config_overrid:6,add_elastix:0,add_elastix_sourcesandsink:0,add_evalu:[0,6,69,70],add_feature_calcul:[0,64],add_parameters_to_grid:2,add_preprocess:0,add_segmentix:0,add_tool:0,addchangeord:17,added:[9,17,24,61,62,64,70],addexcept:59,addinf:61,adding:[2,17,62,64,69,70],addit:[0,6,38,59,61,62,66,69,70],addition:[1,9,10,61,62,70],address:59,adequ:64,adher:61,adjust:[2,10,61,62,70],adopt:[2,15,54,61,62],advanc:[59,69,70],advancedsampl:[0,59],advantag:62,advic:[52,60,62,64,69,70],affect:2,affin:17,after:[0,2,9,38,60,61,62,64,65,66,69,70],afterward:[6,9],again:[62,66,68,69],age:[41,62,66,70],agesex:10,aggreg:66,agument:11,aim:59,aka:70,alejandro:66,alex:66,algorithm:[2,15,60,61,62,68],align:70,all:[0,1,2,6,9,10,11,21,24,38,40,44,48,53,57,58,60,61,62,63,64,65,66,68,69,70],allign:70,allow:[2,6,61,66,67],allow_non:2,along:[9,68],alpha:[2,10],alpha_new:2,alpha_old:2,alreadi:[60,62,68,70],als:70,also:[0,2,6,9,34,54,59,60,61,62,64,65,66,68,69,70],alter:[2,11,61,62,66],altern:70,although:68,alwai:[2,9,61,68,69,70],among:[2,9,10,59,62],amount:[66,68],anaconda:[65,69],analys:69,analysi:[34,59,62,66,70],analyticsvidhya:62,angl:[42,62,66],angu:59,angular:66,ani:[2,9,10,21,39,48,61,62,65,66,68,69,70],annual:59,anoth:[11,60,68,70],anova:2,any_structur:2,anymor:61,anyth:68,anywai:9,apach:59,api:[54,60,62],appear:66,append:[61,62,70],appendix:2,appli:[0,2,6,9,11,38,50,60,61,62,66,68],applic:[11,59,66,68],approach:[9,59,62,68],appropri:0,arbitrari:66,area:[15,66,70],arg:[1,2,4,11,15,18],argmax:10,argu:66,argument:[0,1,2,11,61,64,65],arif:59,around:[2,6,17,56,60,62,64,70],arrai:[1,2,9,10,11,15,59],artefact:66,articl:[15,59,66],arxiv:[9,59],asm:66,aspect:66,assertionerror:0,assess:[6,9,61],assign:[2,40,42,62],assist:[59,66],associ:2,assum:[2,9,50,60,62,65,68,69,70],assumesameimageandmaskmetadata:[11,37,38,62],assumpt:[2,38,62,70],attribut:[0,2,4,6,7,9,11,17,18,59,61],atyp:70,auc:[2,15,70],author:15,auto:[2,53,62],autom:59,automat:[0,6,11,40,59,60,61,62,66,68,69],avail:[2,6,61,63,68],averag:[10,61],average_precision_weight:[39,62],avoid:[2,60,66],awai:66,axes:66,axi:[9,50,62,66],axial:[11,49,50,51,56,60,61,62,66],back:[61,65],backend:[38,61,62],backward:61,balanc:70,band:[6,70],bangma:59,barchart:[10,61,70],base:[0,2,4,5,6,7,9,10,11,17,18,34,50,59,61,62,66,70],baseestim:[2,9],baselin:68,basesearchcv:2,basesearchcvfastr:2,basesearchcvjoblib:2,basestr:6,basi:70,basic:[64,66,68,70],basicworc:[0,59,61,69,70],batch:[9,23,24,60,62],bay:[24,62],bbox_2d:10,bca:70,been:[0,9,10,59,66,68,69],befor:[0,2,6,9,42,60,61,62,65,66,68,69],beforehand:66,begin:[59,61],beginn:59,behavior:2,behaviour:61,being:[15,50,62],belong:[0,2,9],below:[0,2,34,48,60,62,66,68,69,70],benefit:[60,66,68],bengio:70,benign:59,bent:59,berlin:66,besid:[0,59,62,70],best:[2,10,61,62,63,68],best_estim:2,best_estimator_:2,best_index_:2,best_params_:2,best_score_:2,beta:2,better:61,between:[2,9,17,21,22,34,42,59,61,62,66],bia:[2,11,50,60,61,62],bias_correct_imag:11,biascorrect:[49,50,62],biascorrection_mask:[49,50,62],big:61,bigr:[6,40,62,69],bigr_erasmusmc:2,bigrclusterdetector:4,bin:[52,59,62,64],binari:[2,6,9,10,11,59,61,69],binary_classif:[6,69],binaryimag:11,bincount:[51,52,62],binwidth:[51,52,62],bio:59,biomark:[59,66,68],biomed:59,bit:61,bitbucket:2,bitwise_xor:61,black:59,blazev:59,blob:[11,56,60,62,64],block:69,blog:62,bme:59,bmia:69,boht:66,bonferonni:9,book:59,bool:2,boolean_uniform:2,boost:[22,61,62],boostrap:61,bootstrap:[3,10,20,59,61,70],bootstrap_metr:10,bootstrap_n:10,border:60,borderlinesmot:[2,53,62],both:[2,10,59,60,61,62,64,66,68,70],bound:[11,17],boundari:[9,10,11,34,42,62],box:[17,59,62],boxplot:[10,61],braband:59,braf:59,branch:[0,22,62],breviti:69,british:59,broad:66,brought:68,bug:61,bugfix:61,buggi:61,build:[0,17,59,61,68,69,70],build_config:7,build_train:0,built:69,buisman:59,bulletin:9,busy:66,button:59,c_valu:2,cache_s:2,cad:2,caddementia:2,calc_pvalu:15,calcfeat_nod:0,calcfeatur:[37,61,62],calcfeatures_test:[0,12],calcul:[0,2,9,10,38,62,64],call:[2,61,64,66,69,70],callabl:2,can:[0,2,6,9,10,11,17,34,38,42,44,50,59,60,61,62,64,65,66,68,69,70],cancer:[59,66],candid:2,cannot:[2,59,60,61],captur:60,carcinoma:59,cardin:61,cartesiu:[6,69],cartesiusclusterdetector:4,caruana:[2,10],cash:[62,68],cast:61,castillo:59,categor:[9,61],categori:70,caught:6,center:[59,66],centr:66,certain:[2,17,60,61,62,66,70],cf_pyradiom:[37,62],challeg:2,challeng:[2,70],chang:[6,59,60,62,64,66,69],changelog:59,chapter:[6,59,60,62,63,65,66,67,69,70],characterist:[10,15,70],check:[2,6,11,48,50,60,61,62,64,70],check_image_orient:11,check_multimetric_scor:2,check_scor:2,checkorient:[49,50,62],checkspac:[49,50,62],chi2:61,child:[22,62],choic:[2,59,68],choos:[2,50,61,62],chosen:[2,62,66],chunk:2,chunksdict:2,circular:66,class_i:2,class_j:2,class_weight:2,classfic:[40,62],classif:[0,3,6,17,22,46,61,64,66,69,70],classifi:[0,2,10,21,22,32,59,61,62,65,70],classifier_data:2,classifiermixin:2,classpi:2,clean:[54,61,62],clf:2,clinic:68,clip:[11,49,50,60,61,62],clip_imag:11,clipping_rang:[49,50,62],clone:69,closest:2,cluster:[2,6,22,40,61,62,68,69],cnb_alpha:[21,22,62],coars:[6,66,69],coarse_overrid:7,code:[60,62,69],coef0:2,coeffici:[2,9,70],col:[22,62],coliag:[41,42,58,62],coliage_featur:[9,57,58,62],collabor:59,colleagu:68,color:10,colorect:59,column:[2,6,9,59,66,70],com:[6,9,15,38,59,62,64,65,66,69,70],combat:[0,3,16,24,37,38,59,61],combatharmon:[9,38,62],combatmatlab:9,combatpython:9,combin:[1,2,9,10,24,31,32,59,61,62,63,66,68,70],combine_featur:1,combine_method:[1,31,32,62],combine_multiple_estim:10,comma:[2,9,21,23,35,36,41,62],command:[0,2,9,17,59,61,62,64,65,68,69],common:[2,6],commonli:66,commun:69,compact:66,compar:[15,68],comparison:[59,66],compat:[1,7,9,11,60,61,64],complementari:66,complementnb:[22,62],complementnd:[21,62],complet:[61,62,69,70],complex:[66,70],compon:[9,17,34,60,62,68,70],comprehens:[60,63,66],comput:[0,2,6,9,10,15,16,42,52,59,60,61,62,66,68,69,70],compute_ci:[0,59],compute_confid:10,compute_confidence_bootstrap:10,compute_confidence_logit:10,compute_ground_truth_statist:15,compute_midrank:15,compute_midrank_weight:15,compute_statist:10,concept:[59,68],concern:68,concord:70,conda:65,condit:65,conduct:[2,61,70],confer:[59,66,70],conffid:61,confid:[6,10,61,70],config:[0,1,2,6,7,9,10,11,17,22,34,60,61,62,63,64,66,69,70],config_file_path:[1,11],config_io_classifi:[0,59,64],config_io_combat:[0,59],config_io_pyradiom:[0,59],config_preprocess:[0,59],config_segmentix:[0,59],config_worc:[0,59],configbuild:[0,6,61],configpars:[0,11,62],configur:[0,1,2,6,9,59,60,61,64,65,67,69,70],confipars:1,congress:59,congruenc:66,connect:59,consist:[2,39,40,62,69,70],consol:7,constant:[9,43,62,68],construct:[2,6,10,59,69],construct_classifi:[0,59],construct_svm:2,consumpt:2,contain:[0,1,2,6,9,10,11,36,61,62,66,69,70],containingfor:2,content:[7,11,59,66],continu:[2,61,69],contour:[10,11,56,60,62],contrast:[2,66],contribut:59,control:2,converg:[10,61],convers:61,convert:[1,7,9,61,64,66],convert_config_pyradiom:1,convert_features_icc_threshold:9,convert_predict:9,convert_pyradiom:9,convert_pyradiomics_featurevector:9,convert_radiomix_featur:7,convex:66,copi:[0,2,9,11,38,59,60,61,62,64],copymetadata:0,core:[2,6,38,40,61,62,66,69],coron:[51,62],correct:[11,24,50,60,61,62,70],correctli:[10,61,65,70],correl:[9,15,66,68,70],correspond:[2,9,10,40,52,61,62,66,70],cost:2,could:[61,65,66,68],count:[6,52,62,66],count_num_subject:6,count_paramet:10,coupl:70,cours:70,covari:15,cox:70,cpu:2,crash:[59,61,69],creat:[0,2,5,6,10,17,61,62,66,68,69,70],creata:2,create_bbox:17,create_ensembl:[2,61],create_example_data:[0,59,70],create_links_addon:17,create_links_standalon:17,create_network:[13,17],create_param_grid:2,create_random_featur:5,create_sourc:62,createfixedsplit:[0,59],creation:[59,61,66],criteria:59,criterion:2,crop:68,cross:[0,2,10,17,26,38,40,61,62,70],cross_valid:[37,38,62],crossval:[0,59],crossval_typ:10,crossvalid:[3,59],csv:[6,9,10,61,69,70],csv_file_path:4,csv_out:9,csvdetector:4,ct001:0,ct002:0,cto:59,current:[0,2,9,11,26,32,50,59,60,61,62,65,68,70],curv:[6,10,15,61,70],curve_threshold:10,custom:[2,51,52,62],custom_config_overrid:7,cv_iter:2,cv_results_:2,cyan:10,dai:65,dat:9,data:[0,2,9,10,11,16,26,59,60,61,62,66,68,69],data_path:69,datadir:69,datadownload:[0,59,61,69],datafil:61,datafold:[5,69],datafram:[2,10],dataset:[0,2,6,30,38,40,59,60,61,62,68,69,70],datatyp:[61,64,67],datayp:61,dcm:11,deal:[60,61],debug:[10,38,59,61,62,69],debugdetector:4,decent:68,decid:[66,68],decision_funct:2,decision_function_shap:2,decod:66,decomposit:[0,6,59,61,70],decompositon:61,default_queu:65,default_scor:2,defaultconfig:[0,7,62,64,70],defin:[0,2,4,6,7,9,11,17,18,34,56,62,63,64,66,68,69,70],definit:[9,59,66],degre:[2,22,42,62,66],del:69,delai:2,delet:[2,59,61,64],delete_cc_para:2,delete_nonestimator_paramet:2,delong:[0,59],delong_roc_test:15,delong_roc_vari:15,demand:2,dementia:2,demo_param:2,demonst:2,den:59,depend:[0,2,10,59,61,65,68,70],deprec:61,depth:[22,62],der:59,describ:[0,2,63,66,67,70],descript:[2,9,20,22,24,26,28,30,32,34,36,38,40,42,44,46,48,50,52,54,56,58,60,62,64,66,69],descriptor:66,design:68,desmoid:59,despit:59,detail:[2,6,10,11,60,62,65,66,70],detect:[61,65,66],detector:[0,6,59,61,69],determin:[1,2,6,10,11,20,28,32,34,36,38,42,44,46,48,50,52,56,59,61,62,66,68,69,70],determinist:2,develop:[2,66,68],developp:61,deviat:[9,42,62,66],diagnosi:59,diagnost:59,diamet:66,dicom:[0,41,42,50,58,59,60,61,62,70],dicom_featur:[9,57,58,61,62],dicom_feature_label:[41,42,62,66],dicom_feature_tag:[41,42,62,66],dict:[0,1,2,9,11],dictionari:[0,1,2,6,10,11,61,62,70],did:[61,64,68,70],didn:61,differ:[2,10,11,15,59,60,61,68],differenti:59,difficult:68,difscal:9,digit:66,dilat:[11,50,55,56,60,61,62,70],dilate_contour:11,dilate_roi:11,dimens:66,dimension:68,direct:[61,66],directli:[6,66,68,69,70],directori:[0,6,62,69],dirnam:69,disabl:[52,61,62],disc:[50,56,62],discret:[42,62,66],discrete_uniform:2,discrimin:59,discuss:[60,66,70],dispatch:2,dissimilar:66,distanc:[9,34,42,62,66],distance_p:9,distinguish:[2,59,70],distribut:[2,61,64,69,70],distrubit:2,divers:68,divid:68,do_detect:4,do_test_rs_ensembl:2,do_valid:18,doc:64,docstr:70,doctest:2,document:[2,6,9,60,61,63,65,69,70],doe:[2,9,61,62,65,66],doi:9,doing:[2,62],don:69,done:[0,2,60,61,62,63,64,66,68,70],down:61,download:[61,69],download_headandneck:[5,69],download_project:5,download_subject:5,dpi:10,draw_network:70,drawback:66,drawn:[2,40,62],drmaa:[40,62],drmaaplugin:65,drop:61,drug:66,dti:61,dtrf:59,due:[2,61,68],dummi:61,dure:[2,40,61,62,65],dwarkas:59,e104:66,e107:66,each:[2,6,9,10,11,42,61,62,65,66,68,69,70],earlier:[66,69],easi:[59,68],easier:[61,68,70],easili:[61,62,68,69,70],echo:66,ecr:59,edg:[42,62,66],edit:[69,70],editelastixtransformfil:61,edwardo:2,effect:59,effici:[2,61,66],effort:68,efron:70,eigen:[21,62],either:[0,2,9,10,24,34,62,69,70],ejrad:[],elasticnet:[21,22,61,62],elasticnet_alpha:[21,22,62],elasticnet_l1_ratio:[21,22,62],elastix4:[37,62],elastix:[0,37,59,61,62,70],elastix_para:0,elastix_test:[0,12],electr:66,element:[9,34,50,62,70],elif:[65,69],ellip:66,ellipsi:2,ellipt:66,elong:66,els:[64,65],emb:64,embed:[60,61,63],emper:[24,62],emphasi:66,empir:70,emploi:2,empti:2,emptygraylevel:65,enabl:[2,6,52,62],encod:[2,48,62],end:[59,64],energi:66,engin:[2,59,68],enhanc:66,enough:2,ensembl:[2,3,10,17,28,40,59,61,68],ensemble_scor:10,ensur:0,enter:[2,11],entir:2,entri:59,entropi:66,environ:65,epsilon_insensit:[21,62],equal:[2,9,22,24,28,50,62,66],erasmu:68,error:[2,6,10,16,59,61,66,69,70],error_scor:2,especi:[2,38,59,61,62],establish:[59,66],estim:[0,6,7,10,17,21,22,28,34,40,59,61,62],estimator_input:2,estimator_scoring_overrid:7,estsiz:10,etc:[2,9,10,59],etcetera:69,european:59,eusomii:59,evalu:[0,2,3,6,10,30,40,59,61,69],evaluatevalid:18,even:66,everi:[38,62,68],everywher:64,exact:2,exampl:[0,2,6,10,11,15,16,17,48,59,61,62,65,66,68,69],example_stwstrategyhn:69,exampledata:[0,59,69,70],examplefil:69,excel:[66,70],except:[0,6,61],exclud:[9,24,32,34,62],excluded_featur:[23,24,62],exctract:66,exe:[23,62],execut:[0,2,6,16,17,21,22,24,59,61,62,64,68,69],execute_first:7,executionplugin:65,exhaust:2,exist:[17,61,68],exp:2,exp_uniform:2,expand:[10,61,66],expect:[68,69],expected_hostnam:4,experi:[2,6,16,59,61,66,70],experiment:[30,62],experiment_fold:69,experiment_nam:69,expert:66,explain:[34,62],explant:66,explicit:2,explor:2,explos:2,expon:[2,22,62],express:2,extens:[61,68,69],extrac:60,extract:[1,2,6,9,10,11,42,52,56,59,60,61,62,68,70],extract_boundari:10,extract_firstord:[51,52,62],extract_shap:[51,52,62],extractnlargestblobsn:[0,59],extractor:[51,52,62],extrat:11,f1_score:61,f1_weight:[2,6,39,62],f1_weighted_predictproba:[2,39,62],f6d255a45dd:62,facad:[0,7,59,61,69,70],facilit:[59,68],factor_valid:18,fail:61,fals:[1,2,5,9,10,11,17,19,21,22,25,29,31,37,39,41,44,47,49,50,51,55,57,59,62,69],familiar:68,fancyimput:9,faq:[59,61],fashion:69,fast:[2,15,59],fastdelong:15,fastr3:61,fastr:[0,2,6,17,21,22,40,59,61,62,64,65,69,70],fastr_plugin:[0,2,17,21,22,62],fastr_tempdir:[0,62],fastr_test:[0,12],fastr_tool:[0,12],fastrconfig:[0,59,62,70],fastrhom:62,fat:66,fator:2,fatsat:66,fault:61,feat:1,feat_in:9,feat_out:9,feat_out_0:59,feat_test:2,feat_train:2,featpreprocess:[3,59],featsel:[3,59],featur:[0,1,2,5,6,7,9,10,11,16,17,24,32,34,36,38,42,44,48,51,52,58,59,60,61,62,68,69],feature_fil:[6,69],feature_file_nam:6,feature_label:[2,9,10,69],feature_label_1:10,feature_label_2:10,feature_labels_tofit:[9,47,48,62],feature_select:[9,34,62],feature_set:9,feature_valu:[2,9,69],featurecalcul:[37,38,62,64],featureconvert:[0,59,64],featurefil:[1,10],featurefile_p1:69,featurenam:10,featureprocess:[0,59,64],features_:69,features_from_radiomix_xlsx:6,features_from_this_directori:[6,69],features_in:9,features_mod1_patient1:1,features_mod1_patient2:1,features_mod2_patient1:1,features_mod2_patient2:1,features_out:9,features_p1:69,features_test:70,features_test_in:9,features_test_out:9,features_train:70,features_train_in:9,features_train_out:9,featuresc:[3,59],featuresdatadir:69,featurevector:9,feel:[68,69],fellow:68,felt:68,fetur:[11,66],few:68,fewer:66,fibromatosi:59,fibrosi:59,fiduzi:59,field:[1,2,9,11,36,48,60,61,62,64,66,68,69],fig:10,figsiz:10,figur:[10,61,68],figwidth:10,fij:9,file1:[2,9],file2:[2,9],file3:[2,9],file:[0,1,2,5,6,9,10,11,46,59,60,61,62,64,66,69],file_io:[0,59,61],file_path:6,filenam:[10,11,65,70],filepath:[10,61],filesmatlabr2015bbinmatlab:[23,62],filesystem:61,fill:[56,60,62],fill_valu:9,fillhol:[55,56,62],filter:[42,59,62,68],finalbsplineinterpolationord:61,find:[2,16,59,61,63,65,68,69],find_exampledatadir:16,find_testdatadir:16,findlabeldata:11,first:[6,9,10,15,34,52,59,61,62,66,68,69,70],fit:[2,9,30,40,61,62,63,64,66,70],fit_and_scor:[2,63,64],fit_param:2,fit_threshold:10,fit_tim:2,fitandscor:[0,59,61,63,64],fitfailedwarn:2,fittd:2,fitted_workflow:2,five:[64,68],fix:[2,10,17,26,34,52,59,62,65,68,70],fixandscor:61,fixed_se:[2,25,26,62],fixed_splits_csv:6,fixedsplit:2,flag:61,flat:66,flatten:[10,61],flatten_object:10,fleiss:9,flexibl:[61,68],flip:[10,66],fluctuat:66,focu:70,focuss:70,fold:2,folder:[2,7,10,16,61,62,64,69,70],follow:[2,9,10,59,60,62,64,65,66,68,69,70],fontsiz:[9,10],force2d:[51,52,62],force2ddimens:[51,52,62],foremost:66,foresight:68,forest:[34,62],fork:65,form:66,format:[0,1,2,5,6,7,9,10,11,59,60,61,62,64,65,70],formula:2,forward:68,found:[2,59,61,62,68,69,70],foundat:59,four:68,fpr:10,fractal:[58,61,62],fractal_featur:[9,57,58,62],framework:[59,61,68],frangi:[42,62,66],free:69,freeli:70,frequenc:[42,62,66],frequent:9,from:[0,1,2,6,7,9,10,11,15,21,24,38,40,42,46,56,59,60,61,62,64,65,66,68,69,70],frozenset:[2,4,9,18],fulfil:2,full:[6,7,10,11,38,49,50,59,60,61,62,69],fulli:[59,61],fullprint:7,fun:68,function_bas:59,funtion:9,further:61,furthermor:66,futur:61,gabor:[42,58,59,61,62],gabor_angl:[41,42,62,66],gabor_frequ:[41,42,62,66],gamma:[2,22,62],garcia:2,gastrointestin:59,gather:10,gaussian:[52,59,62],gaussiannb:[21,62],gave:[2,61],gclm:[48,62,66],gener:[0,2,3,6,9,10,21,22,27,34,50,59,60,61,64,65,66,68,70],generalis:59,generaliz:59,generate_config:64,generate_feature_boxplot:10,generate_performance_boxplot:10,genet:[11,70],geometrytoler:[51,52,62],get:[2,10,11,59,68,69,70],get_r:11,getparametermap:17,gibhub:59,git:69,github:[1,2,6,9,10,11,15,38,59,62,64,65,69,70],give:[2,48,60,61,62,65,66,68,69,70],given:[0,2,6,9,10,40,42,59,61,62,64,66,69,70],glcm:[42,48,52,58,59,62,65],glcm_angl:[41,42,62,66],glcm_distanc:[41,42,62,66],glcm_level:[41,42,62,66],glcmm:66,gldm:[52,58,59,62,65],gldzm:[58,61,62],glob:[6,69],glrlm:[42,52,58,59,62,65],glszm:[42,52,58,59,62,65],gmean:[39,62],going:68,good:70,grade:59,grahpviz:61,grai:59,grand:2,graphviz:61,grayscal:[42,62],grid:[2,40,62],grid_scor:61,gridsearch:[22,62],gridsearchcv:2,gridsearchcvfastr:2,gridsearchcvjoblib:2,griethuysen:66,grlm:66,ground:[10,70],ground_truth:15,groundtruth:2,group:[2,9,34,61,62,66,68,70],groupsel:[2,64],groupwis:[2,61,66,70],groupwisesearch:[33,34,62],growth:59,gsout:2,guarante:2,guid:[2,59,62],guidelin:70,hack:65,had:[61,68],haibo:2,halton:2,haltonsampl:2,hand:68,handbook:59,handl:[9,61],handle_unknown:9,hanff:59,happen:66,harmon:[0,9,16,38,59,60,61,62],has:[0,2,6,9,50,59,62,65,66,68],have:[0,2,9,10,11,34,38,59,60,61,62,64,65,66,68,69,70],hdf5:[1,2,6,7,9,10,59,69,70],head:[69,70],header:[0,2,6,66,70],heidelberg:66,held:2,help:[2,4,7,9,11,17,61,70],helper:[0,6,59],henc:[2,6,9,10,60,61,62,64,66,68,70],hepatocellular:59,herder:59,here:[2,60,62,63,64,66,70],hf_mean:9,high:[59,66,68,69],higher:2,highest:2,highli:[2,68],highlight:[51,52,62],hing:[21,62],histogram:[2,41,42,58,59,62],histogram_featur:[9,57,58,62],histopatholog:59,histori:68,hofland:59,hold:[0,2],hole:[56,60,62],home:61,homogen:[22,62,66],hope:59,horribl:69,hospit:[23,62],host:59,hostnamedetector:4,hot:[48,62],hounsfield:62,how:[1,2,10,11,28,42,56,61,62,64,66,68,69,70],howev:[2,60,62,64,66,68,70],htm:62,html:[0,9,21,22,34,42,51,52,60,62],http:[0,2,6,9,15,21,22,34,38,42,51,52,54,59,60,62,64,65,69,70],huber:[21,62],hyper:[2,62],hyperoptim:[3,28,40,59,60,61],hyperparamat:2,hyperparamet:[2,10,40,61,62,63,66,68],hypothes:66,hypothesi:15,i_max:10,i_min:10,icc:[2,9,16,59,61,70],icc_anova:2,iccthreshold:[0,59],icctyp:[2,9],idea:[68,70],ident:2,identifi:[6,69],ids:[2,11],ieee:[2,15,59,66],ignor:[9,62],iid:2,iivarinen:66,illustr:68,imag:[0,2,6,10,11,17,38,42,50,52,59,61,62,68,69],image_featur:[2,9,10],image_features_test:2,image_features_train:2,image_file_nam:[6,69],image_mr:70,image_typ:[41,42,62],imagedatadir:69,imagefeatur:[3,59,66,70],imagefil:11,images1:70,images_from_this_directori:[6,69],images_test:70,images_train:[0,6,70],imagetyp:62,imaginary_label_1:69,imbalanc:[2,54,61,62],img2:10,img:[10,11],immedi:2,implement:[0,2,6,9,11,15,22,24,62,68,70],implicitli:68,imposs:2,improv:[2,66],imput:[0,2,3,44,59,61,64,68],imputat:2,incekara:59,includ:[0,2,6,11,28,32,60,61,62,64,66,68,69,70],incompat:[52,62],incorpor:61,incorrect:[50,61,62],incorrectli:[10,61,70],increas:[2,40,61,62],inde:66,independ:[68,70],index:[2,9,10,59,62,66,70],indexerror:[0,59],indic:[2,11],individu:2,ineffici:68,infer:[0,40,59,62,70],infinit:61,influenc:66,info:[6,62,65],inform:[2,9,10,38,59,62,64,66,69,70],informat:59,ini:[0,1,2,9,11,61,62,64],init:[9,64],init_adasyn:2,init_borderlinesmot:2,init_nearmiss:2,init_neighbourhoodcleaningrul:2,init_randomoversampl:2,init_randomundersampl:2,init_smot:2,init_smoteenn:2,init_smotetomek:2,initi:[0,2,4,6,7,9,11,17,61,66],inner:[42,60,62,66],input:[0,2,6,9,10,11,17,59,61,62,64,65,68],input_fil:[7,11],inputarrai:9,inset:61,insight:70,inspect:61,instal:[59,60,61,62],instanc:[0,2],instanti:2,instead:[2,52,60,61,62,66,69,70],integ:[2,6,9,10,11,19,21,25,27,28,33,37,39,40,41,42,43,44,49,51,52,53,55,59,61,62],integr:[59,61,68],intellig:66,intens:[11,50,52,60,62,66],inter:[2,9],interact:[6,59,61,69],interest:66,interfac:2,intermed:10,intermedi:2,intermediatefacad:61,intern:[59,66,70],interpol:[11,51,52,62],interpret:[64,68],interquartil:66,interv:[6,10,61,70],intervent:[59,66],intra:[2,9],intraclass:[9,70],introduct:[59,69],introductori:68,invalidcsvfileexcept:7,invalidlabelsvalid:18,invalidorderexcept:7,invari:66,inverse_transform:2,involv:2,ioerror:0,iopars:[0,2,59,64],ioplugin:0,iri:2,is_empti:2,is_multimetr:2,is_train:6,isbi:59,isi:70,isn:61,issu:[59,61,65,68,69,70],item:[0,2,9,69],iter:[2,10,20,22,38,40,61,62,64,70],ith:2,itk:[0,11,61],itkimag:10,its:[2,68],itself:[66,68,70],jacob:66,jalv:59,jfortin1:[9,38,62],jiaj:66,job:[2,6,40,61,62],joblib:[2,22,38,61,62],joblib_backend:[37,38,62],joblib_ncor:[37,38,62],join:69,joost:66,joseph:9,journal:[15,59,66],json:[2,11,61,69],jth:2,jukka:66,just:[10,61,64,69,70],k_neighbor:[2,53,54,62],kapsa:59,keep:[2,11,59,61,68],kei:[2,3,41,61,62,70],kept:9,kernel:[2,22,62,70],kessel:59,keyerror:0,kfold:2,kind:[61,68],klein:59,knn:[9,43,44,61,62],knnimput:61,know:62,knowledg:2,known:66,kovesi:66,kurtosi:66,kwarg:[2,4,18],label1:[45,62,70],label2:[45,62,70],label:[0,1,2,3,6,9,10,11,15,24,46,48,51,52,59,60,61,66,68,69],label_1_count:15,label_data:[2,10,11],label_data_test:2,label_data_train:2,label_fil:[2,10,11,17,69],label_info:11,label_nam:[1,2,6,11,45,46,62,69],label_process:[0,59],label_s:2,label_set:9,label_statu:11,label_typ:[0,1,2,9,10,11,17,70],labelprocess:61,labels_from_this_fil:[6,59,69],labels_test:[9,70],labels_train:[9,70],lambda:2,lambda_tol:2,languag:[23,24,59,62,68],laplacian:[52,59,62],laptop:68,larg:[2,61,66,68],larger:[40,61,62,66],largest:[10,11,56,60,62,66],lasso:[2,21,33,34,62],last:[61,66,68],lastli:[50,62,64],later:[2,9,62,66],latest:[42,51,52,60,62],latex:61,latter:64,lbfg:[21,62],lbp:[42,58,59,62],lbp_npoint:[41,42,62,66],lbp_radiu:[41,42,62,66],lda:[21,22,62],lda_shrinkag:[21,22,62],lda_solv:[21,22,62],lead:66,learn:[2,9,10,21,22,34,54,59,60,61,62,68,70],least:[2,66,68],leav:[26,61,62],led:61,leender:59,left:[2,61],length:[2,9,10,59],lengthi:69,lesion:[32,62,66],less:[61,62,66],let:69,letter:15,level:[42,51,52,59,62,70],lib:59,licens:59,lidc:59,lightweight:2,lij:9,like:[2,9,61,62,66,68,69],limit:70,line:[2,9,59,60,64,66,68,69],linear:[2,21,61,62,70],linear_model:[21,22,34,62],linearexecut:[6,17,21,62],link:[17,61,64,69,70],link_n4biasfieldcorrection_doc:60,linr:[21,62],linstretch:[0,59],linux:61,linuxdetector:4,lipoma:59,liposarcoma:59,list:[0,1,2,4,6,7,9,10,11,17,18,21,23,35,36,38,41,42,44,47,58,62,65,70],literatu:9,literatur:[9,60,66],littl:[2,68],liver:[59,70],load:[1,11,42,62,69],load_config:[1,64],load_config_xnat:11,load_data:1,load_featur:[1,61],load_iri:2,load_label:11,load_label_csv:11,load_label_txt:11,load_label_xnat:11,loc:[2,21,22,33,43,53,54,62],local:[42,59,62],locat:[6,58,61,62,66,69],location_featur:[9,57,58,62],log10:15,log:[9,15,22,41,42,51,52,58,59,61,62,64,65,68],log_featur:[9,57,58,62],log_sigma:[41,42,62,66],log_uniform:2,log_z_scor:[35,62],logarithm:[9,61],logic:61,logist:[22,62],logisticregress:[21,22,34,61,62],logit:9,logstandardscal:9,longer:[61,62],loo:[25,26,61,62],loo_cross_valid:2,look:[6,59,60,62,63,64,66,68,69,70],loop:[2,65],loss:[2,22,62,66],lot:[52,62,66,68],low:[59,66],lower:[9,11,34,50,61,62],lowerbound:11,lr_l1_ratio:[21,22,62],lr_solver:[21,22,62],lrc:[21,22,62],lrpenalti:[21,22,62],lsqr:[21,62],luckili:68,lung:59,maarten:59,machin:[2,34,59,61,62,66,68,70],macskassi:70,made:[6,59,61,62,66,68,70],maenpaa:66,magnet:66,mai:[2,62,64,66,68,69],main:[6,10,13,16,60,61,69,70],major:[53,61,62,66],majorli:[6,61],make:[2,6,10,38,40,60,61,62,64,65,68,69,70],make_scatterplot:10,make_scor:2,malign:59,manag:[0,66],mandatori:[1,2,9,10,11],manhattan:61,manhattan_import:10,mani:[0,2,9,10,28,56,60,61,62,66,68,70],manipul:70,mann:70,mannwhitneyu:[9,33,62],manual:[2,6,39,59,60,61,62,65,66,68,69],manufactur:66,map:[2,10,70],mappingproxi:[0,2,4,6,7,9,11,17,18],mark:10,marku:66,martijn:59,mask:[0,2,10,11,38,50,52,55,56,60,61,62,68,69],mask_contour:11,masked_arrai:2,masks_test:70,masks_train:70,mass:66,master:[2,60,64,70],match:[1,11,61,62,70],matlab:[9,11,23,24,59,60,62,68],matplotlib2tikz:61,matplotlib:10,matrix:[2,9,59],matter:9,matti:66,max:[1,31,32,34,41,62,64,66],max_it:[2,21,22,62],maxim:2,maximum:[2,22,42,61,62,66],maxlen:[2,39,40,61,62],mean:[1,2,6,9,24,31,32,43,61,62,65,66,70],mean_fit_tim:2,mean_score_tim:2,mean_test_scor:2,mean_train_scor:2,measur:[2,6,66,70],median:[9,43,50,62,66],medic:[59,66,68],medicin:[59,66],meet:[6,59],melanoma:59,member:2,memori:[2,39,40,61,62,70],mention:66,mesenter:59,mesh:66,messag:[2,10,61],metadata:[0,11,38,50,60,61,62,66],metadata_fil:11,metadata_test:70,metadata_train:70,metaestimatormixin:2,metastas:59,method:[0,2,6,9,10,11,15,32,34,36,44,49,50,53,54,59,61,62,65,66,68,70],metion:9,metric1:10,metric1t:10,metric2:10,metric2t:10,metric:[0,9,10,27,28,39,40,59,61,62,70],mhd:[11,70],miccai:59,michael:66,miclea:59,micro:68,microsoft:69,middl:[0,10,70],midrank:15,mimic:11,min:[9,34,41,61,62,64,66],min_object_s:[55,56,62],mine:[59,60,68],minim:[2,42,62,69,70],minimum:[22,42,50,56,61,62,66],minkov:9,minm:[49,62],minmax:[9,35,61,62],minor:[53,61,62,66],minsubjectsvalid:18,mismatch:[38,62],miss:[2,9,61],missing_valu:9,missingpi:[9,61],mixtur:11,mod:[9,23,24,61,62,64],modal:[2,9,42,52,61,62,66,70],modalityname1:[2,9],modalityname2:[2,9],mode:6,model:[1,2,6,10,15,17,34,40,58,59,61,62,68,70],model_select:[2,9],moder:[24,60,62,66],modified_hub:[21,62],modnam:1,modu:[0,2,10,17,45,46,62,69],modul:[12,21,22,34,61,62,64,70],modular:59,modulenotfounderror:59,molecular:59,momentum:66,more:[2,6,9,10,11,36,38,40,59,60,61,62,64,65,66,68,69,70],moreov:68,morpholog:[11,66],most:[2,6,9,22,62,66,68,69],most_frequ:[9,43,62],mostli:[2,9,61,62,70],mount:[2,6,61,69],move:61,mr001:0,mr002:0,mri:[52,59,62,66],mse:70,mstarmans91:[6,59,64,65,69,70],much:[40,54,61,62,66],multi:[2,59,66],multi_class_auc:2,multi_class_auc_scor:2,multi_class_relief:9,multicentr:59,multiclass:[2,6,70],multicor:[6,38,62],multihread:61,multilabel:[2,6,45,46,59,61,62],multilabel_typ:10,multimetric_grid_search:2,multimod:61,multipl:[0,2,9,10,32,38,60,61,62,66,68,69,70],multipli:[11,55,56,62],multiprocess:[37,62],multiresolut:66,multiscal:66,multislic:[42,58,62],multivendor:59,must:[2,59,62],mutat:59,mutlicor:2,mwu:9,mxn:2,n_1:10,n_2:10,n_blob:[55,56,62],n_classifi:15,n_compon:61,n_core:2,n_exampl:15,n_featur:[2,5,9,61],n_iter:[2,17,19,20,25,26,39,40,62],n_job:2,n_jobspercor:[2,39,40,62],n_jobsperscor:2,n_neighbor:[2,9,43,44,53,54,62],n_neighbour:9,n_neightbor:9,n_object:5,n_output:2,n_patient:9,n_sampl:[2,9,61],n_split:[2,39,40,61,62],n_splits_:2,n_test:10,n_train:10,nadeau:70,naiv:68,name:[0,2,6,9,10,11,17,22,24,36,42,48,57,58,59,61,62,66,69,70],name_of_label_predicted_for_evalu:70,nan:[2,9,32,44,61,62,66],ndarrai:2,nearest:[9,34,44,62],nearmiss:[53,62],neccesari:[61,64],neck:69,need:[2,6,9,59,61,62,64,66,68,69,70],needaccess:9,neg:[9,61,70],neg_dual_func:2,neighbor:[9,34,44,62],neighborhood:59,neighbour:[9,66],neighbourhoodcleaningrul:[2,53,62],net:9,nettyp:17,network:[0,13,17,59,61,62,64,68,69],neural:70,neurocombat:60,never:[30,60,62],new_spac:11,newest:61,newli:61,nework:0,next:[66,69,70],ngldm:[58,61,62],ngtdm:[42,52,58,59,61,62,65],nice:[61,68],niessen:59,nifti:[61,70],nii:[0,6,11,69,70],nipyp:2,nmod:0,nocrossv:2,node:[0,17,32,61,62,68,70],nofeaturesfoundexcept:7,noimagesfoundexcept:7,nois:[24,62],nomean:9,non:[2,6,9,24,61,62,66,68,70],none:[0,1,2,4,5,6,7,9,10,11,15,17,18,21,35,51,55,56,61,62,65],nonparametr:70,nor:59,norm_tol:2,normal:[2,10,11,49,50,51,52,60,61,62,66,68,70],normalization_factor:10,normalize_imag:[11,60],normalize_roi:[11,49,50,62],normalize_whitespac:2,normalizescal:[51,52,62],nosegmentationsfoundexcept:7,not_label:2,notabl:61,note:[0,2,6,9,10,11,61,62,66,68,69],notic:66,notimplementederror:0,now:[61,66],npoint:66,npv:[61,70],nrrd:[11,70],nsampl:10,nsubject:[5,69],num_class:2,num_train:2,number:[2,6,9,10,11,15,20,22,26,34,38,40,42,44,54,61,62,66,68,70],numbertoextract:11,numer:[2,9,70],numf:9,numpi:[2,9,10,11,15,59,61,66],obj:59,object:[0,1,2,4,6,7,9,10,11,17,18,22,32,54,56,59,60,61,62,64,69],objectsampl:[0,59,61],observ:[2,9],obsolet:[38,62],occur:[2,9,34,59,62,63,65,70],occurr:9,odd:66,oddfeat:9,oddpati:9,odink:59,oerat:15,of_:[23,62],off:[2,66,70],offer:66,offici:59,often:[62,66,68,70],ojala:66,older:61,omit:69,onc:[2,11,60,61,66],oncolog:59,oncoradiom:[6,61],one:[0,2,6,9,10,11,26,36,48,50,61,62,64,65,66,68,69,70],onehotencod:[2,3,9,48,59,61],onehotencoderwrapp:[0,59],onevsrest:61,onevsrestclassifi:2,onli:[2,6,9,11,22,30,40,50,61,62,65,66,68,69,70],onlin:[68,69],ontolog:68,onward:2,open:[59,61,65,68,69],oper:[10,11,59,66,70],opim:2,optim:[0,2,22,40,60,61,62,63,66,70],optimiz:0,option:[0,1,2,6,9,10,11,19,21,22,23,25,27,29,31,32,33,35,37,39,41,43,45,47,49,51,53,55,57,60,61,62,64,66,69,70],order:[2,9,10,11,52,60,61,62,63,66,68],org:[2,9,21,22,34,62],organ:[66,68],orient:[11,41,42,50,58,59,60,61,62],orientation_featur:[9,57,58,62],orientationprimaryaxi:[49,50,62],origin:[2,51,52,58,60,61,62,66],original_featur:[9,57,58,62],oserror:0,other:[0,2,9,34,39,59,60,61,62,64,68,70],otherwis:[2,9,50,52,60,61,62],otsu:[11,49,50,61,62],our:[59,62,64,66,69,70],out:[2,10,11,26,61,62,68,69,70],outcom:[2,40,62,68,69],outer:[26,60,62,66],outlier:[9,61],output:[2,6,9,10,11,17,61,62,64,68,69,70],output_csv:[9,10],output_fold:7,output_hdf:2,output_itk:10,output_json:2,output_nam:10,output_name_zoom:10,output_png:[9,10],output_tex:[9,10],output_zip:10,outputfold:[2,10,69],over:[2,6,9,61,62,66,68],overal:[61,69],overfit:[30,60,61,62],overfit_scal:[2,10],overfitscal:[29,30,62],overid:61,overlai:10,overrid:[6,61],oversampl:[61,68],overview:[60,63,66,69,70],overwrit:[6,50,61,62],overwritten:0,own:[37,62,64,66,68,69],p_ngtdm:65,packag:[59,61,66,70],packagedir:61,pad:[10,17],padmo:59,page:[15,59,68,70],pairwis:11,pairwise_auc:2,panda:[2,10,69],panda_data:2,paper:[2,9,66],par:[9,23,24,62],para:2,paracheck:10,parallel:[2,6,61,62],param:[2,10],param_c:2,param_degre:2,param_distribut:2,param_gamma:2,param_grid:2,param_kernel:2,param_list:2,paramet:[0,2,6,9,10,11,22,34,40,54,59,60,61,62,63,64,68,70],parameter_optim:[0,59],parametergrid:2,parameters_al:2,parameters_est:2,parametersampl:2,parametr:[9,24,62],paramt:2,parekh:66,parent:17,pars:[1,61,62,64],part:[2,34,42,61,62,63,64,66,68,70],parti:9,pass:[2,61,70],path:[0,1,2,7,9,10,11,24,61,62,69],pathnotfoundexcept:7,patient001:0,patient002:0,patient1:[62,70],patient1_0:70,patient1_1:70,patient2:[62,70],patient3:[62,70],patient:[0,1,2,6,9,10,11,32,54,59,61,62,66,69,70],patient_001:69,patient_002:69,patient_featur:[9,61,70],patient_id:[2,11,17],patientclass:[61,62],patientinfo:[1,2,9,10,11],patientinfo_test:2,patientinfo_train:2,patrick:9,pattern:[59,70],pca:[2,6,34,61,62,64,70],pcatyp:[33,34,62],pce:61,pdf:9,peak:66,pearson:70,peform:69,penalti:[22,61,62],peopl:59,per:[0,1,2,9,24,56,61,62,65,66,70],per_featur:[9,23,24,62],percentag:[2,6,9,10,17,26,34,40,54,61,62,66,69,70],percentil:[9,61,66],perform:[0,2,6,9,10,17,26,30,38,40,46,59,61,62,63,68,69,70],performance_all_0:69,performance_fil:69,performance_metr:2,performance_multilabel:2,performance_singlelabel:2,person:59,peter:66,peura:66,pf_:[23,35,62],phase:[41,42,58,59,62],phase_featur:[9,57,58,62],phase_minwavelength:[41,42,62,66],phase_nscal:[41,42,62,66],phd:68,phenotyp:66,phil:59,philip:66,physic:0,pick:[62,70],pid:[10,11,61],pietikainen:66,pilot:59,pinfo:[10,17,61],pinfo_hn:69,pip:[60,61,65,69],pipelin:[0,59,61,68,70],pixel:[0,10,42,52,62,66],place:64,placehold:9,platform:[59,68,69],pleas:[2,6,9,59,60,62,63,64,65,66,69,70],plot:[0,9,16,59,61],plot_bar:10,plot_barchart:[0,59],plot_boxplot_featur:[0,59],plot_boxplot_perform:[0,59],plot_error:[0,59],plot_estimator_perform:[0,59],plot_hyperparamet:[0,59],plot_im_and_overlai:10,plot_imag:[0,59,61],plot_prc_cic:10,plot_pvalues_featur:[0,59],plot_ranked_imag:10,plot_ranked_percentag:10,plot_ranked_posterior:[10,61],plot_ranked_scor:[0,59],plot_roc:[0,59],plot_roc_c:10,plot_single_prc:10,plot_single_roc:10,plot_svm:61,plot_svr:61,plot_test:9,plotminmaxrespons:[0,59],plotrankedscor:61,plu:[2,24,62,70],pluge:0,plugin:[0,2,21,22,40,61,62,65,68],png:[0,10,61],point:[2,10,42,62,69],pointint:10,pointsar:10,poli:[2,21,62],polynomi:[22,62,70],port:61,posit:[2,9,10,34,62,66,70],possibl:[2,9,59,61,66,68,70],post:69,posterior:[6,10,70],posteriors_csv:10,potenti:64,ppv:70,practic:68,prax:66,prc_csv:10,prc_png:10,prc_tex:10,pre:61,pre_dispatch:2,precis:[10,61,66,70],precomput:69,precrop:[51,52,62],predict:[2,5,6,9,10,15,37,57,59,60,61,62,65,66,68,69,70],predict_label:[6,61,69],predict_log_proba:2,predict_proba:[2,61],predictions_on:15,predictions_sorted_transpos:15,predictions_two:15,predictproba:61,predit:61,preflighcheck:61,preflightcheck:[0,59,61],prepar:[11,59],preprint:59,preprocess:[0,2,3,9,37,38,50,59,61,68,70],preprocess_nod:0,preprocessor:[0,32,59,61,62,64],preprocss:2,present:[2,59,61,66],preserverd:[24,62],prevent:61,previou:[68,70],previous:[61,68],primari:[50,62],primary_axi:11,princip:66,principl:[34,59,62,68,70],print:[2,7,9,10,61,69,70],probabl:[2,15,69],probe:59,problem:[2,59,61,68],procedur:[9,62,70],proceed:[59,70],process:[0,2,6,15,38,59,60,61,62,68,70],process_fit:2,processpoolexecut:17,produc:[2,66],program:[23,62,68],progress:[2,61],project:[5,11,61],project_nam:5,projectid:[45,46,62],proof:59,proper:[0,61],properli:61,properti:[2,66],prostat:59,proven:68,provid:[0,2,6,10,11,17,24,28,38,49,50,60,62,63,66,69,70],provost:70,pseudo:2,psycholog:9,publish:15,purpos:[0,30,62],push:59,put:[10,61,62,70],pvalu:15,pxcastconvert:61,pyradiom:[1,3,9,37,51,52,57,59,61,64,65,66],python3:61,python:[5,9,23,59,60,61,62,64,68,69],python_intro:60,pywavelet:65,qda:[21,22,62],qda_reg_param:[21,22,62],qualiti:2,quantifi:66,quantit:[59,66,68],question:68,quick:[59,62],quickli:66,quit:[62,68],qxm:2,radial:[66,70],radian:[42,62,66],radii:[42,62],radiograph:66,radiolog:[59,66],radiom:[0,9,60,62,63,70],radiomix:[6,7,61],radiu:[10,11,42,50,56,62,66],rais:[2,61],rajic:59,ran:[2,61,69],random:[2,5,24,26,34,61,62,70],random_se:2,random_search:2,random_search_paramet:2,random_split:[25,62],random_split_cross_valid:2,random_st:[2,9],randomizedsearchcv:2,randomizedsearchcvfastr:2,randomizedsearchcvjoblib:2,randomli:[2,34,62],randomoversampl:[53,62],randomsearch:2,randomst:2,randomundersampl:[53,62],rang:[10,11,22,34,54,62,66],rank:[6,9,10,28,34,40,61,62,68,70],rank_:2,rank_test_scor:2,ranked_pid:10,ranked_scor:10,ranked_truth:10,rankedposterior:61,rankedsvm:[0,59,61],ranking_scor:[2,39,40,62],ranksvm:2,ranksvm_test:2,ranksvm_test_origin:2,ranksvm_train:2,ranksvm_train_old:2,rate:[10,22,62,70],rater:9,rather:2,ratio:[10,22,62,66],rational:63,raw:[11,66],rbf:[2,21,62],read:[1,2,11,68,69,70],read_hdf:69,reader:61,readthedoc:[0,42,51,52,54,59,60,61,62],reason:[2,66],recal:[10,61,70],receiv:[10,15,70],recommend:[2,22,24,59,60,62,64,66,68,69],recommmend:69,recreat:2,reduc:[2,59,61],reduct:[61,68],redund:[61,66],ref:2,refactor:61,refer:[0,1,2,3,4,6,7,9,10,11,15,17,18,37,61,62,64,66,68],refit:[2,40,61,62],refit_and_scor:2,refit_ensembl:10,refit_workflow:[2,39,40,62],reflect:66,regard:59,regardless:69,region:66,registr:[0,38,59,61,62,68,70],registrationnod:[37,38,62],regress:[2,6,10,17,22,46,59,61,62,69,70],regressor:[0,59,60,61],regular:[22,62,70],rel:2,relat:[0,66],releas:[61,68],relev:[60,64,66,68,70],reli:66,reliabl:9,relief:[0,2,34,59,61,62],reliefdistancep:[33,34,62],reliefnn:[33,34,62],reliefnumfeatur:[33,34,62],reliefsamples:[33,34,61,62],reliefsel:2,reliefus:[33,34,62],remov:[9,10,38,56,60,61,62],remove_small_object:[55,56,62],removeconst:10,renam:61,rencken:59,repeat:[2,62],repetit:66,replac:[2,9,44,61,62,64,65],replacenan:[2,61],report:70,repositori:[59,69],repres:[2,66],reproduc:[61,68],requir:[0,2,6,22,59,61,62,65,68,69,70],resampl:[2,3,11,49,50,54,59,60,61,70],resample_imag:11,resampled_imag:11,resampledpixelspac:[51,52,62],resampling_spac:[49,50,62],research:[59,66,68],resourc:[0,11,13,59,65,68],respect:[2,9,56,60,62,69,70],result:[2,9,10,38,50,59,61,62,66,68],ret:2,retreiv:11,retriev:66,return_al:2,return_estim:2,return_n_test_sampl:2,return_paramet:2,return_tim:2,return_train_scor:2,returnplot:10,revert:61,review:66,rfmax_depth:[21,22,62],rfmin_samples_split:[21,22,62],rfn_estim:[21,22,62],rfr:[21,62],rgrd:[58,61,62],rgrd_featur:[9,57,58,62],ridg:[21,61,62],right:70,ring:[11,55,56,60,61,62],risk:[59,70],rms_score:2,rng:2,robust:[9,35,59,61,62,66],robust_z_scor:[9,35,62],robustscal:[9,61],robuststandardscal:[9,61],roc:[6,10,15,61,70],roc_comparison:15,roc_csv:10,roc_png:10,roc_tex:10,roi:[11,50,52,59,61,62,70],roi_dilate_radiu:11,roidetermin:[11,49,50,62],roidil:[49,50,62],roidilateradiu:[49,50,62],rokwa:9,root:[2,6],rosset:70,rotat:[50,62,66],rough:66,round:[2,22,61,62],rounded_list:2,routin:[66,68],row:[2,9,66],rtstructread:61,run:[2,6,9,59,61,62,65,68,70],runtim:[2,61],rvs:2,safe:64,saga:[21,62],sagit:[51,61,62],sai:60,same:[1,2,9,10,22,32,38,60,61,62,66,68,69,70],samefeat:9,sampl:[0,1,2,9,10,22,34,40,54,61,62,70],sample_s:9,sample_weight:15,sampler:2,sampleswarn:18,sampling_strategi:[2,53,54,62],sar:2,sar_scor:2,sarcoma:59,satur:66,save:[0,2,5,9,10,38,40,61,62,66,69,70],save_config:[0,64],save_data:2,save_memori:10,scale:[2,9,21,22,33,36,42,43,52,53,54,61,62,66,68],scaler:[0,2,30,59,61,62,64],scaling_method:[35,36,62],scan:[62,66,69],scanner:66,scatterplot:[0,59],schoot:59,scienc:70,scikit:[2,9,21,22,34,60,62],scipi:2,score:[2,6,9,10,17,40,50,61,62,63,70],score_tim:2,scorer:2,scorer_:2,scorers_dict:2,scoring_method:[2,6,7,39,40,62],scoring_paramet:2,script:[9,60,61,64,65,68,69,70],script_path:69,scroll:70,search:[2,6,9,34,40,59,61,62,64,65],searchcv:[0,10,59,61,64],sebastian:59,second:[2,9,15,24,62,66],section:[62,69,70],see:[0,1,2,4,6,7,9,10,11,17,21,22,34,38,42,51,52,54,59,60,61,62,64,65,66,69,70],seed:[2,26,61,62],seem:[61,68],seen:[2,70],seg:[17,61],seg_liver_mr:70,seg_tumor1_mr:70,seg_tumor2_mr:70,seg_tumor_mr:70,segment:[0,6,10,11,17,38,56,60,61,62,66,68,69],segmentation_file_nam:[6,69],segmentations1:70,segmentations2:70,segmentations_from_this_directori:[6,69],segmentations_test:70,segmentations_train:[6,70],segmentix:[0,1,3,37,38,52,59,60,61,70],segmentix_test:[0,12],segradiu:[55,56,62],segtyp:[55,56,62],sel:9,select:[2,6,9,11,22,34,52,59,61,62,68,70],selected_label:6,selectfeatgroup:[3,34,59],selectfrommodel:[33,34,61,62],selectfrommodel_estim:[33,34,62],selectfrommodel_lasso_alpha:[33,34,62],selectfrommodel_n_tre:[33,34,62],selectgroup:[0,59],selectindividu:[0,59],selectmodel:2,selectmulticlassrelief:9,selectormixin:9,self:[2,4,7,9,11,17,22,62,65],selfeat_vari:9,semant:[0,6,58,59,61,62],semantic_featur:[9,57,58,62],semantics_from_this_fil:6,semantics_test:70,semantics_train:70,semf_:[23,35,62],semicolon:61,sensibl:66,sensit:70,separ:[2,6,21,23,30,35,36,41,61,62,70],sequenc:[0,2,70],seri:6,seriou:60,serpar:61,serv:[0,66,68,70],session:5,set:[0,1,2,5,6,9,10,15,17,22,30,38,40,44,50,60,61,62,64,65,66,68,69,70],set_fixed_split:6,set_multicore_execut:[6,69],set_tmpdir:[6,69],settin:2,settings_dict:1,setup:[6,61],sever:[0,6,9,11,60,61,62,65,66,68,70],sex:[9,41,62,66,70],sf_:[23,62],sf_compact:9,sgd:[21,22,62],sgd_alpha:[21,22,62],sgd_l1_ratio:[21,22,62],sgd_loss:[21,22,62],sgd_penalti:[21,22,62],sgdr:[21,62],shape:[2,9,41,42,52,58,59,62],shape_featur:[9,57,58,62],shear:68,sheet:70,shift:[24,62],should:[0,1,2,6,9,10,11,24,36,38,40,42,54,56,60,61,62,70],show:[2,10,61,69,70],shown:68,shrink:2,shrinkag:[22,62],shrout:9,shuffle_estim:10,shutil:61,siemen:66,sigma:[9,15,66],sign:[2,9],signal:15,signatur:[2,4,7,9,11,17,59],signific:[10,70],significantli:62,similar:[2,9,60,61,64,65,66,68,69,70],similarli:64,simpl:[6,60,66,68,69],simpleelastix:70,simpleitk:[50,60,62,70],simpler:68,simplest:70,simplevalid:18,simpleworc:[0,59,60,61,69,70],simpli:[24,59,61,62,65,69,70],simplifi:69,simultan:[2,68],singel:6,singl:[2,6,10,11,15,24,40,42,44,59,60,61,62,63,70],single_class_relief:9,singleclass:2,singlelabel:[2,17,45,46,62],singleton:2,sink:[0,17,61,64,68,70],sink_data:[0,13,17,70],site:[2,59],sitkbsplin:[51,52,62],six:66,size:[2,10,17,34,40,42,59,61,62,70],size_alpha:2,skew:66,skip:[36,61,62,69,70],skip_featur:[9,35,36,62],sklearn:[2,9,10,21,22,34,39,61,62,64],slack:[22,62],sleijfer:59,slice:[0,2,10,56,61,62,66,70],slicer:[0,10,59,61],slight:2,slightli:69,slow:61,small:[9,56,60,61,62,66],smaller:[54,62,66],smallest:2,smart:[10,62],smit:59,smote:[2,53,61,62],smoteen:2,smoteenn:[53,62],smotetomek:[53,62],snapshot:70,sne:[6,70],societi:59,soft:59,softwar:[24,59,62,68],sole:66,solid:66,solut:[2,65],solv:[65,68],solver:[22,61,62],some:[0,2,6,61,62,64,68,69,70],somenam:[62,70],someon:68,sometim:61,sort:[2,15,61,69],sourc:[0,1,2,4,5,6,7,9,10,11,13,15,16,17,18,59,61,62,64,66,68,69],source_data:[0,13,70],space:[2,9,10,11,34,50,60,61,62,64,66,70],span:2,spars:[9,70],spawn:[0,2],spawner:0,spearman:70,specif:[2,9,22,48,62,64,65,66,68,69,70],specifi:[0,2,6,11,22,34,38,40,48,54,62],speed:[6,69],spend:2,spheric:66,split0_test_scor:2,split0_train_scor:2,split1_test_scor:2,split1_train_scor:2,split2_test_scor:2,split2_train_scor:2,split:[2,9,17,22,26,61,62,66,68,70],springer:66,squar:[2,10,70],squared_epsilon_insensit:[21,62],squared_hing:[21,62],squared_loss:[21,62],src:2,ssh:69,stabl:[0,9,21,22,34,54,61,62],stack:1,standalon:[17,61],standard:[6,9,42,59,61,62,66,69,70],standardis:59,standardscal:9,starman:59,start:[2,59,61,62,65,68],stat:[2,10,69],state:[0,2,28,61,62,64,69],statement:[11,64],staticmethod:18,statist:[0,2,9,10,16,34,59,61,62,66,69,70],statisticalsel:2,statisticaltest:61,statisticaltestfeatur:[0,59,61],statisticaltestmetr:[33,34,62],statisticaltestthreshold:[0,33,34,59,62],statisticaltestus:[33,34,62],statsticaltestthreshold:61,statu:[2,11,59],std:9,std_fit_tim:2,std_score_tim:2,std_test_scor:2,std_train_scor:2,stefan:59,step:[2,42,60,61,62,63,66,68,70],still:[61,69,70],stimul:59,stop:[11,61],store:[2,6,7,69,70],str:[2,61],straight:[60,68],strategi:[2,9,10,43,44,54,59,61,62],stratif:59,stratifi:[2,17],stratifiedkfold:2,strenght:[22,62],strength:[22,62,66],stretch:10,string:[0,1,2,6,9,10,11,21,23,35,39,40,41,45,47,61,62,70],stromal:59,strongli:69,struct:61,structer:66,structur:[66,69,70],stuck:69,student:[9,68,70],studi:[0,59,68],studio:69,stwstrategyhn1:69,sub:[0,66],subfold:[6,61,69],subgroup:66,subject:[2,5,6],subkei:[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,62],subpackag:59,subset:69,substr:[9,24,36,48,62],subtract:[11,55,56,61,62],succeed:61,success:2,suffici:70,suggest:[2,64],suit:[0,2,11],suitabl:[59,66],sun2014fast:15,sun:15,suppli:[1,2,10,42,50,54,56,61,62,70],support:[2,9,26,50,59,61,62,65,66,68,70],suppos:62,sure:[6,64,65,70],surfac:66,surfsara:69,surgeri:59,surgic:59,surrog:2,surround:66,surveil:59,surviv:[6,10,59,70],svc:2,svd:[21,62],svm:[2,6,10,21,22,61,62],svmc:[21,22,62],svmcoef0:[21,22,62],svmdegre:[21,22,62],svmgamma:[21,22,62],svmkernel:[21,22,62],svr:[2,6,21,62],symlink:61,symmetri:66,symposium:59,synthet:[9,10],synthetictest:9,system:[0,2,62,66,70],tabl:[2,70],tadpol:[2,70],tag:[41,42,61,62,66,70],take:[2,9,40,61,62,64,70],taken:10,tandfonlin:9,target:2,task:68,techniqu:[62,66],tedious:68,tell:[6,64,70],tempdir:[61,69],tempfold:2,temporari:[0,6,61,69],tempsav:[2,37,38,62],term:[22,34,61,62,68],terminolog:59,test:[0,2,6,9,10,15,26,30,34,38,40,59,61,62,69,70],test_combat:[0,59],test_combat_fastr:16,test_data:2,test_help:[0,59],test_iccthreshold:[0,59],test_invalidlabelsvalidator_columnsubstr:16,test_invalidlabelsvalidator_patientcolumn:16,test_invalidlabelsvalidator_patientsubstr:16,test_invalidlabelsvalidator_validconfig:16,test_metr:10,test_plot_error:[0,59],test_rs_ensembl:2,test_sampl:10,test_sample_count:2,test_scor:[2,39,62],test_score_dict:2,test_siz:[2,17,25,26,39,40,62],test_target:2,test_valid:[0,59],tex:[10,61],text:2,textur:[42,58,59,62],texture_featur:9,texture_gabor:[41,42,62],texture_gabor_featur:[9,57,58,62],texture_glcm:[41,42,51,52,62],texture_glcm_featur:[9,57,58,62],texture_glcmm:[41,42,62],texture_glcmms_featur:[9,57,58,62],texture_gldm:[51,52,62],texture_gldm_featur:[57,58,62],texture_gldzm_featur:[9,57,58,62],texture_glrlm:[41,42,51,52,62],texture_glrlm_featur:[9,57,58,62],texture_glszm:[41,42,51,52,62],texture_glszm_featur:[9,57,58,62],texture_lbp:[41,42,62],texture_lbp_featur:[9,57,58,62],texture_ngldm_featur:[9,57,58,62],texture_ngtdm:[41,42,51,52,62],texture_ngtdm_featur:[9,57,58,62],tf_glcm_contrastd1:66,than:[2,54,61,62],thei:[2,61,62,63,66,69,70],them:[2,61,62,68,70],themselv:66,therebi:[59,61,68,70],therefor:[0,6,9,60,61,64,66,68,69,70],thi:[0,2,6,9,10,32,36,40,48,50,54,59,60,61,62,63,64,65,66,67,68,69,70],thick:66,thing:[61,62,69],third:9,thoma:59,thomeer:59,those:[2,6,9,64,66,70],thread:[37,61,62],three:[2,66],thresh:[9,10],threshold:[2,9,10,16,34,50,54,61,62,66],threshold_annot:10,threshold_clean:[2,53,54,62],through:[0,2,11,17,50,59,61,62,66,68,69,70],throughput:66,thu:[2,9,59,60,61,62,66,68,70],tibshirani:70,tiff:[11,70],tikzplotlib:61,timbergen:59,time:[2,10,26,34,40,54,61,62,66,68,69,70],timer:61,timo:66,tip:59,tissu:59,titl:15,tmp:6,tmpdir:[6,69],todo:[2,9],togeth:[61,64],tol:2,toler:2,tomek:2,tomographi:59,tone:59,too:66,tool:[0,6,37,38,59,60,61,62,64,67,68,69,70],toolbox:[9,57,58,59,61,62,65,66,70],top50:2,top:[10,61],topi:66,toshiba:66,total:[2,66],towardsdatasci:62,tpr:10,trace:[65,69],track:2,trade:2,train:[0,2,6,10,22,26,30,34,38,40,61,62,70],train_data:2,train_scor:2,train_score_dict:2,train_target:2,train_test_split:2,trainclassifi:[0,10,59,61,64],transact:[2,66],transform:[2,9,38,61,62,64,66,70],transformationnod:[37,38,62],transformermixin:9,transformix:[0,37,59,61,62],transpos:[11,60,61],transpose_imag:11,travi:61,treat:62,tree:[22,34,62,70],tri:[2,68],trick:59,trigger:66,truth:[2,10,61,70],tsampl:10,ttest:[9,33,61,62],tube:66,tubular:66,tumor:[59,69,70],tumour:59,tune:[2,62,68],tupl:2,turn:61,tutori:[16,59,62,65],two:[0,2,9,10,15,21,33,41,43,53,61,62,66,69,70],txt:[0,1,2,6,9,10,61,62,70],type:[0,2,4,7,9,10,11,17,22,25,26,34,38,59,61,62,64,66,68,70],typeerror:[0,2],typegroup:61,typic:70,typo:61,udr:2,unadjust:15,unaffect:[24,62],unag:11,uncorrect:70,under:[2,15,59,61,62,66,70],underli:2,underscor:70,understand:68,unfit:2,unfortun:65,uniform:[2,22,54,61,62,64,66],uniformli:2,uniqu:[2,66],unit:[61,62],univari:[2,6,70],univers:[2,59],unless:2,unreleas:59,unround:61,unsuccesful:61,unsuit:61,unsupervis:2,until:2,updat:61,upgrad:61,upon:[6,62],upper:[34,62],upperbound:[11,50,62],uri:61,url:[11,45,46,61,62],urltyp:61,usabl:2,usag:[2,40,61,62,66,70],usd:9,use:[0,2,6,9,10,11,17,20,22,24,26,28,30,32,34,38,43,44,48,50,52,58,60,61,62,64,66,68,69,70],use_fastr:2,useag:9,used:[0,1,2,6,9,10,11,22,26,28,30,34,38,40,42,44,46,50,52,54,56,58,59,61,62,64,66,68,69,70],useful:[2,9,38,62,70],usemask:11,usepca:[33,34,62],user:[2,6,60,66,67,69],usersmynamefeaturefold:6,usersmynameimagefold:6,usersmynamesegmentationfold:6,uses:[2,6,9,61,64,65,66,67],using:[0,2,6,9,17,22,24,26,28,34,40,44,50,52,59,60,61,62,64,65,66,68,69,70],usual:66,util:2,v600e:59,val:0,valid:[0,2,6,9,10,17,26,38,40,59,61,62,70],validationm:[26,62],validatorsfactori:18,valu:[0,2,6,9,10,11,15,34,39,42,44,48,52,60,61,62,64,66,69,70],value1:62,value2:62,valueerror:0,van:[59,66],vari:[2,52,61,62,66,68],variabl:[0,10,24,60,61,62,69],varianc:[2,9,15,33,34,61,62,66],variancethreshold:[0,34,59,61,62],variancethresholdmean:9,variant:68,variat:[24,62],varieti:[59,66],variou:[2,10,59,61,62,64,67,68,70],varsel:2,vector:[2,9],veenland:59,veldt:59,vendor:59,verbos:[2,5,9,10,61],verhoef:59,veri:[2,68],vermeulen:59,version:[15,24,61,62,65,66],verson:61,versu:59,vessel:[41,42,58,59,62],vessel_featur:[9,57,58,62],vessel_radiu:[41,42,62,66],vessel_scale_rang:[41,42,62,66],vessel_scale_step:[41,42,62,66],vfs:[0,61],via:69,vincent:59,virtual:65,virtualenv:69,vishwa:66,visit:64,visser:59,visual:[66,69],vizual:61,vol:70,volum:[15,59,66],voort:59,voxel:[56,62,66],voxelarrayshift:[51,52,62],wai:[62,66,70],want:[0,6,11,59,60,62,66,69,70],warn:[2,61],warp:70,wavelength:[42,62],wavelet:[51,52,58,59,61,62],wavelet_featur:[9,57,58,62],weak:[0,2,4,6,7,9,11,17,18],week:65,weichao:15,weight:[2,22,61,62],weigth:[34,62],welch:[9,33,62,70],well:[11,59,61,62,64,66,68,69,70],were:[61,64,66,68,70],weus:70,what:[64,66],when:[0,2,6,9,10,17,22,26,28,34,36,40,44,60,61,62,64,65,66,68,69,70],whenev:2,where:[2,10,59,61,68,69],wheter:[30,62],whether:[1,2,6,9,10,11,20,28,38,42,46,48,50,52,56,61,62,63,66,69],which:[0,2,6,7,9,10,11,24,34,36,38,40,48,52,60,61,62,63,64,65,66,68,69,70],whitnei:70,whole:[40,62,68],why:62,wich:2,wide:[59,66],width:[52,59,62,70],wijnenga:59,wiki:[1,2,9,10,11],wilcoxon:[2,9,33,62,70],wildcard:6,willemssen:59,window:[22,61,62,69],wip:[9,10,45,46,59,60,62,63,64],with_mean:9,with_std:9,within:[61,63,65,66,68,70],withing:[50,62],without:[2,61],wonder:68,worc:[1,2,4,5,6,7,9,10,11,13,15,16,17,18,22,37,39,42,48,60,61,62,63,64,66,67,68,69],worc_:69,worc_config:[0,59,61,62],worcassertionerror:0,worccastconvert:61,worccastcovert:61,worcdirectorydetector:4,worcerror:0,worcflow:59,worcindexerror:0,worcioerror:0,worckeyerror:[0,59],worcnotimplementederror:0,worcscal:9,worctutori:[6,59,69,70],worctutorialsimple_travis_regress:[0,59],worctypeerror:0,worcvalueerror:[0,59],worcworc:64,work:[11,61,66,68],workaround:2,workflow:[0,2,6,10,40,61,62,63,64,66,68,69,70],would:[62,66,68,69,70],wrap:[2,60,61,64,68],wrapper:[2,60,64,70],write:10,written:[2,9,10],wtype:0,www:[9,62],x_test:[2,9],x_train:[2,9,10],xgb:[22,62],xgb_boosting_round:[21,22,62],xgb_colsample_bytre:[21,22,62],xgb_gamma:[21,22,62],xgb_learning_r:[21,22,62],xgb_max_depth:[21,22,62],xgb_min_child_weight:[21,22,62],xgbclassifi:[21,62],xgboost:[60,61,62],xgbregressor:[21,62],xgdboost:[60,61],xlsx:[2,7],xml:64,xnat:[11,61,69],xnat_url:5,y_predict:[2,10],y_score:[2,10],y_test:2,y_train:[2,9,10],y_truth:[2,10],yandexdataschool:15,year:15,yet:[6,11,61],yield:2,yml:61,you:[0,2,6,11,17,48,54,59,60,61,62,64,65,66,68,69,70],your:[0,2,6,30,37,38,40,46,52,59,61,62,64,65,69],yourself:[59,68],yspace:9,z_score:[9,11,35,49,62],zero:[9,44,61,62],zij:9,zip:[10,61,69],zone:59,zoomfactor:10,zwanenburg:66},titles:["WORC Package","IOparser Package","classification Package","<no title>","detectors Package","exampledata Package","facade Package","helpers Package","fastrconfig Package","featureprocessing Package","plotting Package","processing Package","resources Package","fastr_tests Package","fastr_tools Package","statistics Package","tests Package","tools Package","validators Package","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","WORC: Workflow for Optimal Radiomics Classification","Additional functionality","Changelog","Configuration","Data Mining Methods","Developer documentation","FAQ","Radiomics Features","Resource File Formats","Introduction","Quick start guide","User Manual"],titleterms:{"0rc1":61,"boolean":65,"class":11,"function":60,"import":69,Added:61,Adding:64,The:[69,70],actual:69,addexcept:[0,65],addit:60,advancedsampl:2,analysi:[63,69],arrai:65,attribut:70,basicworc:6,begin:65,bigr:65,bin:66,binari:66,bootstrap:62,calcfeatures_test:13,chang:61,changelog:61,choic:66,classif:[2,59,62,63],classifi:60,cluster:65,column:65,combat:[9,60,62],command:70,compon:63,compute_ci:10,config_io_classifi:1,config_io_combat:1,config_io_pyradiom:1,config_preprocess:1,config_segmentix:1,config_worc:1,configbuild:7,configur:62,construct:70,construct_classifi:2,content:62,crash:65,create_example_data:5,createfixedsplit:[2,17],creation:62,crossval:2,crossvalid:62,data:[63,64,70],datadownload:5,debug:70,decomposit:9,definit:70,delet:65,delong:15,depend:66,detector:4,develop:[59,64],dicom:66,differ:[65,66],dimension:63,document:[59,64],elastix:17,elastix_para:70,elastix_test:13,ensembl:62,entri:65,error:65,estim:2,evalu:[17,62,70],exampl:[64,70],exampledata:5,except:7,execut:[65,70],experi:[65,69],extract:66,extractnlargestblobsn:11,facad:6,fals:65,faq:65,fastr:68,fastr_test:13,fastr_tool:14,fastrconfig:8,feat_out_0:65,featpreprocess:62,featsel:62,featur:[63,64,65,66,70],featureconvert:9,featureprocess:9,featuresc:62,file:[65,67,70],file_io:1,filter:66,first:65,fitandscor:2,fix:[61,66],format:67,found:65,from:63,full:66,function_bas:65,gabor:66,gaussian:66,gener:62,given:65,glcm:66,gldm:66,glrlm:66,glszm:66,grai:66,groupwis:63,guid:69,hdf5:65,helper:[7,11],histogram:66,hyperoptim:[62,64],icc:60,iccthreshold:9,imag:[60,66,70],imagefeatur:62,imput:[9,62,63],indexerror:65,indic:[59,65],infer:17,input:[69,70],instal:[65,69],integ:65,interact:[62,70],introduct:[62,68],iopars:1,job:65,keep:65,label:[62,65,70],label_process:11,labels_from_this_fil:65,laplacian:66,lbp:66,learn:63,length:66,level:66,lib:65,like:65,line:65,linstretch:10,local:66,log:66,look:65,machin:63,manual:70,mask:70,matrix:66,metadata:70,method:[63,64],metric:2,mine:63,model:63,modul:[0,1,2,4,5,6,7,8,9,10,11,13,15,16,17,18,59,65],modular:68,modulenotfounderror:65,must:65,name:65,need:65,neighborhood:66,network:70,ngtdm:66,numpi:65,obj:65,object:70,objectsampl:2,occur:66,onehotencod:[62,63],onehotencoderwrapp:9,optim:[59,68],orient:66,other:66,packag:[0,1,2,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,65,69],paramet:66,parameter_optim:2,patient:65,pattern:66,pca:63,phase:66,plot:10,plot_barchart:10,plot_boxplot_featur:10,plot_boxplot_perform:10,plot_error:10,plot_estimator_perform:10,plot_hyperparamet:10,plot_imag:10,plot_pvalues_featur:10,plot_ranked_scor:10,plot_roc:10,plotminmaxrespons:10,preflightcheck:18,preprocess:[11,60,62],preprocessor:9,princip:63,process:[7,11,64],pyradiom:62,queue:65,quick:69,radiom:[59,66,68],rankedsvm:2,reduct:63,refer:59,registr:60,regress:63,regressor:2,relief:[9,63],resampl:[62,63],resourc:[12,67],result:69,roi:66,run:[66,69],scale:63,scaler:9,scatterplot:10,searchcv:2,segment:70,segmentix:[11,62],segmentix_test:13,select:[63,66],selectfeatgroup:62,selectgroup:9,selectindividu:9,semant:[66,70],shape:66,simpleworc:[6,65],site:65,size:66,slicer:17,some:65,sourc:70,standard:68,start:69,statist:[15,63],statisticaltestfeatur:9,statisticaltestthreshold:9,submit:65,subpackag:[0,6,12],surviv:63,tabl:59,terminolog:68,test:[16,63,64],test_combat:16,test_help:16,test_iccthreshold:16,test_plot_error:16,test_valid:16,textur:66,tip:69,tone:66,tool:17,toolbox:64,trainclassifi:2,transformix:17,trick:69,tutori:69,type:65,univari:63,unreleas:61,used:65,user:[59,70],valid:18,varianc:63,variancethreshold:9,vessel:66,wavelet:66,welcom:59,where:65,width:66,worc:[0,59,65,70],worc_config:8,worckeyerror:65,worctutorialsimple_travis_regress:16,worcvalueerror:65,work:65,workflow:59,would:65,your:70,zone:66}})
\ No newline at end of file
+Search.setIndex({docnames:["autogen/WORC","autogen/WORC.IOparser","autogen/WORC.classification","autogen/WORC.config","autogen/WORC.detectors","autogen/WORC.exampledata","autogen/WORC.facade","autogen/WORC.facade.helpers","autogen/WORC.fastrconfig","autogen/WORC.featureprocessing","autogen/WORC.plotting","autogen/WORC.processing","autogen/WORC.resources","autogen/WORC.resources.fastr_tests","autogen/WORC.resources.fastr_tools","autogen/WORC.statistics","autogen/WORC.tests","autogen/WORC.tools","autogen/WORC.validators","autogen/config/WORC.config_Bootstrap_defopts","autogen/config/WORC.config_Bootstrap_description","autogen/config/WORC.config_Classification_defopts","autogen/config/WORC.config_Classification_description","autogen/config/WORC.config_ComBat_defopts","autogen/config/WORC.config_ComBat_description","autogen/config/WORC.config_CrossValidation_defopts","autogen/config/WORC.config_CrossValidation_description","autogen/config/WORC.config_Ensemble_defopts","autogen/config/WORC.config_Ensemble_description","autogen/config/WORC.config_Evaluation_defopts","autogen/config/WORC.config_Evaluation_description","autogen/config/WORC.config_FeatPreProcess_defopts","autogen/config/WORC.config_FeatPreProcess_description","autogen/config/WORC.config_Featsel_defopts","autogen/config/WORC.config_Featsel_description","autogen/config/WORC.config_FeatureScaling_defopts","autogen/config/WORC.config_FeatureScaling_description","autogen/config/WORC.config_General_defopts","autogen/config/WORC.config_General_description","autogen/config/WORC.config_HyperOptimization_defopts","autogen/config/WORC.config_HyperOptimization_description","autogen/config/WORC.config_ImageFeatures_defopts","autogen/config/WORC.config_ImageFeatures_description","autogen/config/WORC.config_Imputation_defopts","autogen/config/WORC.config_Imputation_description","autogen/config/WORC.config_Labels_defopts","autogen/config/WORC.config_Labels_description","autogen/config/WORC.config_OneHotEncoding_defopts","autogen/config/WORC.config_OneHotEncoding_description","autogen/config/WORC.config_Preprocessing_defopts","autogen/config/WORC.config_Preprocessing_description","autogen/config/WORC.config_PyRadiomics_defopts","autogen/config/WORC.config_PyRadiomics_description","autogen/config/WORC.config_Resampling_defopts","autogen/config/WORC.config_Resampling_description","autogen/config/WORC.config_Segmentix_defopts","autogen/config/WORC.config_Segmentix_description","autogen/config/WORC.config_SelectFeatGroup_defopts","autogen/config/WORC.config_SelectFeatGroup_description","index","static/additionalfunctionality","static/changelog","static/configuration","static/datamining","static/developerdocumentation","static/faq","static/features","static/file_description","static/introduction","static/quick_start","static/user_manual"],envversion:{"sphinx.domains.c":1,"sphinx.domains.changeset":1,"sphinx.domains.cpp":1,"sphinx.domains.javascript":1,"sphinx.domains.math":2,"sphinx.domains.python":1,"sphinx.domains.rst":1,"sphinx.domains.std":1,"sphinx.ext.intersphinx":1,"sphinx.ext.todo":1,"sphinx.ext.viewcode":1,sphinx:56},filenames:["autogen/WORC.rst","autogen/WORC.IOparser.rst","autogen/WORC.classification.rst","autogen/WORC.config.rst","autogen/WORC.detectors.rst","autogen/WORC.exampledata.rst","autogen/WORC.facade.rst","autogen/WORC.facade.helpers.rst","autogen/WORC.fastrconfig.rst","autogen/WORC.featureprocessing.rst","autogen/WORC.plotting.rst","autogen/WORC.processing.rst","autogen/WORC.resources.rst","autogen/WORC.resources.fastr_tests.rst","autogen/WORC.resources.fastr_tools.rst","autogen/WORC.statistics.rst","autogen/WORC.tests.rst","autogen/WORC.tools.rst","autogen/WORC.validators.rst","autogen/config/WORC.config_Bootstrap_defopts.rst","autogen/config/WORC.config_Bootstrap_description.rst","autogen/config/WORC.config_Classification_defopts.rst","autogen/config/WORC.config_Classification_description.rst","autogen/config/WORC.config_ComBat_defopts.rst","autogen/config/WORC.config_ComBat_description.rst","autogen/config/WORC.config_CrossValidation_defopts.rst","autogen/config/WORC.config_CrossValidation_description.rst","autogen/config/WORC.config_Ensemble_defopts.rst","autogen/config/WORC.config_Ensemble_description.rst","autogen/config/WORC.config_Evaluation_defopts.rst","autogen/config/WORC.config_Evaluation_description.rst","autogen/config/WORC.config_FeatPreProcess_defopts.rst","autogen/config/WORC.config_FeatPreProcess_description.rst","autogen/config/WORC.config_Featsel_defopts.rst","autogen/config/WORC.config_Featsel_description.rst","autogen/config/WORC.config_FeatureScaling_defopts.rst","autogen/config/WORC.config_FeatureScaling_description.rst","autogen/config/WORC.config_General_defopts.rst","autogen/config/WORC.config_General_description.rst","autogen/config/WORC.config_HyperOptimization_defopts.rst","autogen/config/WORC.config_HyperOptimization_description.rst","autogen/config/WORC.config_ImageFeatures_defopts.rst","autogen/config/WORC.config_ImageFeatures_description.rst","autogen/config/WORC.config_Imputation_defopts.rst","autogen/config/WORC.config_Imputation_description.rst","autogen/config/WORC.config_Labels_defopts.rst","autogen/config/WORC.config_Labels_description.rst","autogen/config/WORC.config_OneHotEncoding_defopts.rst","autogen/config/WORC.config_OneHotEncoding_description.rst","autogen/config/WORC.config_Preprocessing_defopts.rst","autogen/config/WORC.config_Preprocessing_description.rst","autogen/config/WORC.config_PyRadiomics_defopts.rst","autogen/config/WORC.config_PyRadiomics_description.rst","autogen/config/WORC.config_Resampling_defopts.rst","autogen/config/WORC.config_Resampling_description.rst","autogen/config/WORC.config_Segmentix_defopts.rst","autogen/config/WORC.config_Segmentix_description.rst","autogen/config/WORC.config_SelectFeatGroup_defopts.rst","autogen/config/WORC.config_SelectFeatGroup_description.rst","index.rst","static/additionalfunctionality.rst","static/changelog.rst","static/configuration.rst","static/datamining.rst","static/developerdocumentation.rst","static/faq.rst","static/features.rst","static/file_description.rst","static/introduction.rst","static/quick_start.rst","static/user_manual.rst"],objects:{"WORC.IOparser":{config_WORC:[1,0,0,"-"],config_io_PyRadiomics:[1,0,0,"-"],config_io_classifier:[1,0,0,"-"],config_io_combat:[1,0,0,"-"],config_preprocessing:[1,0,0,"-"],config_segmentix:[1,0,0,"-"],file_io:[1,0,0,"-"]},"WORC.IOparser.config_WORC":{load_config:[1,1,1,""]},"WORC.IOparser.config_io_PyRadiomics":{load_config:[1,1,1,""]},"WORC.IOparser.config_io_classifier":{load_config:[1,1,1,""]},"WORC.IOparser.config_io_combat":{load_config:[1,1,1,""]},"WORC.IOparser.config_preprocessing":{load_config:[1,1,1,""]},"WORC.IOparser.config_segmentix":{load_config:[1,1,1,""]},"WORC.IOparser.file_io":{convert_config_pyradiomics:[1,1,1,""],load_data:[1,1,1,""],load_features:[1,1,1,""]},"WORC.WORC":{Tools:[0,2,1,""],WORC:[0,2,1,""]},"WORC.WORC.Tools":{__dict__:[0,3,1,""],__init__:[0,4,1,""],__module__:[0,3,1,""],__weakref__:[0,3,1,""]},"WORC.WORC.WORC":{__dict__:[0,3,1,""],__init__:[0,4,1,""],__module__:[0,3,1,""],__weakref__:[0,3,1,""],add_ComBat:[0,4,1,""],add_elastix:[0,4,1,""],add_elastix_sourcesandsinks:[0,4,1,""],add_evaluation:[0,4,1,""],add_feature_calculator:[0,4,1,""],add_preprocessing:[0,4,1,""],add_segmentix:[0,4,1,""],add_tools:[0,4,1,""],build:[0,4,1,""],build_training:[0,4,1,""],defaultconfig:[0,4,1,""],execute:[0,4,1,""],save_config:[0,4,1,""],set:[0,4,1,""]},"WORC.addexceptions":{WORCAssertionError:[0,5,1,""],WORCError:[0,5,1,""],WORCIOError:[0,5,1,""],WORCIndexError:[0,5,1,""],WORCKeyError:[0,5,1,""],WORCNotImplementedError:[0,5,1,""],WORCTypeError:[0,5,1,""],WORCValueError:[0,5,1,""]},"WORC.addexceptions.WORCAssertionError":{__module__:[0,3,1,""]},"WORC.addexceptions.WORCError":{__module__:[0,3,1,""],__weakref__:[0,3,1,""]},"WORC.addexceptions.WORCIOError":{__module__:[0,3,1,""],__weakref__:[0,3,1,""]},"WORC.addexceptions.WORCIndexError":{__module__:[0,3,1,""]},"WORC.addexceptions.WORCKeyError":{__module__:[0,3,1,""]},"WORC.addexceptions.WORCNotImplementedError":{__module__:[0,3,1,""]},"WORC.addexceptions.WORCTypeError":{__module__:[0,3,1,""]},"WORC.addexceptions.WORCValueError":{__module__:[0,3,1,""]},"WORC.classification":{AdvancedSampler:[2,0,0,"-"],ObjectSampler:[2,0,0,"-"],RankedSVM:[2,0,0,"-"],SearchCV:[2,0,0,"-"],construct_classifier:[2,0,0,"-"],createfixedsplits:[2,0,0,"-"],crossval:[2,0,0,"-"],estimators:[2,0,0,"-"],fitandscore:[2,0,0,"-"],metrics:[2,0,0,"-"],parameter_optimization:[2,0,0,"-"],regressors:[2,0,0,"-"],trainclassifier:[2,0,0,"-"]},"WORC.classification.AdvancedSampler":{AdvancedSampler:[2,2,1,""],boolean_uniform:[2,2,1,""],discrete_uniform:[2,2,1,""],exp_uniform:[2,2,1,""],log_uniform:[2,2,1,""]},"WORC.classification.AdvancedSampler.AdvancedSampler":{__dict__:[2,3,1,""],__init__:[2,4,1,""],__iter__:[2,4,1,""],__len__:[2,4,1,""],__module__:[2,3,1,""],__weakref__:[2,3,1,""]},"WORC.classification.AdvancedSampler.boolean_uniform":{__dict__:[2,3,1,""],__init__:[2,4,1,""],__module__:[2,3,1,""],__weakref__:[2,3,1,""],rvs:[2,4,1,""]},"WORC.classification.AdvancedSampler.discrete_uniform":{__dict__:[2,3,1,""],__init__:[2,4,1,""],__module__:[2,3,1,""],__weakref__:[2,3,1,""],rvs:[2,4,1,""]},"WORC.classification.AdvancedSampler.exp_uniform":{__dict__:[2,3,1,""],__init__:[2,4,1,""],__module__:[2,3,1,""],__weakref__:[2,3,1,""],rvs:[2,4,1,""]},"WORC.classification.AdvancedSampler.log_uniform":{__dict__:[2,3,1,""],__init__:[2,4,1,""],__module__:[2,3,1,""],__weakref__:[2,3,1,""],rvs:[2,4,1,""]},"WORC.classification.ObjectSampler":{ObjectSampler:[2,2,1,""]},"WORC.classification.ObjectSampler.ObjectSampler":{__dict__:[2,3,1,""],__init__:[2,4,1,""],__module__:[2,3,1,""],__weakref__:[2,3,1,""],fit:[2,4,1,""],init_ADASYN:[2,4,1,""],init_BorderlineSMOTE:[2,4,1,""],init_NearMiss:[2,4,1,""],init_NeighbourhoodCleaningRule:[2,4,1,""],init_RandomOverSampling:[2,4,1,""],init_RandomUnderSampling:[2,4,1,""],init_SMOTE:[2,4,1,""],init_SMOTEENN:[2,4,1,""],init_SMOTETomek:[2,4,1,""],transform:[2,4,1,""]},"WORC.classification.RankedSVM":{RankSVM_test:[2,1,1,""],RankSVM_test_original:[2,1,1,""],RankSVM_train:[2,1,1,""],RankSVM_train_old:[2,1,1,""],is_empty:[2,1,1,""],neg_dual_func:[2,1,1,""]},"WORC.classification.SearchCV":{BaseSearchCV:[2,2,1,""],BaseSearchCVJoblib:[2,2,1,""],BaseSearchCVfastr:[2,2,1,""],Ensemble:[2,2,1,""],GridSearchCVJoblib:[2,2,1,""],GridSearchCVfastr:[2,2,1,""],RandomizedSearchCVJoblib:[2,2,1,""],RandomizedSearchCVfastr:[2,2,1,""],chunks:[2,1,1,""],chunksdict:[2,1,1,""],rms_score:[2,1,1,""],sar_score:[2,1,1,""]},"WORC.classification.SearchCV.BaseSearchCV":{__abstractmethods__:[2,3,1,""],__init__:[2,4,1,""],__module__:[2,3,1,""],create_ensemble:[2,4,1,""],decision_function:[2,4,1,""],inverse_transform:[2,4,1,""],predict:[2,4,1,""],predict_log_proba:[2,4,1,""],predict_proba:[2,4,1,""],preprocess:[2,4,1,""],process_fit:[2,4,1,""],refit_and_score:[2,4,1,""],score:[2,4,1,""],transform:[2,4,1,""]},"WORC.classification.SearchCV.BaseSearchCVJoblib":{__abstractmethods__:[2,3,1,""],__module__:[2,3,1,""]},"WORC.classification.SearchCV.BaseSearchCVfastr":{__abstractmethods__:[2,3,1,""],__module__:[2,3,1,""]},"WORC.classification.SearchCV.Ensemble":{__abstractmethods__:[2,3,1,""],__init__:[2,4,1,""],__module__:[2,3,1,""],decision_function:[2,4,1,""],inverse_transform:[2,4,1,""],predict:[2,4,1,""],predict_log_proba:[2,4,1,""],predict_proba:[2,4,1,""],transform:[2,4,1,""]},"WORC.classification.SearchCV.GridSearchCVJoblib":{__abstractmethods__:[2,3,1,""],__init__:[2,4,1,""],__module__:[2,3,1,""],fit:[2,4,1,""]},"WORC.classification.SearchCV.GridSearchCVfastr":{__abstractmethods__:[2,3,1,""],__init__:[2,4,1,""],__module__:[2,3,1,""],fit:[2,4,1,""]},"WORC.classification.SearchCV.RandomizedSearchCVJoblib":{__abstractmethods__:[2,3,1,""],__init__:[2,4,1,""],__module__:[2,3,1,""],fit:[2,4,1,""]},"WORC.classification.SearchCV.RandomizedSearchCVfastr":{__abstractmethods__:[2,3,1,""],__init__:[2,4,1,""],__module__:[2,3,1,""],fit:[2,4,1,""]},"WORC.classification.construct_classifier":{construct_SVM:[2,1,1,""],construct_classifier:[2,1,1,""],create_param_grid:[2,1,1,""]},"WORC.classification.createfixedsplits":{createfixedsplits:[2,1,1,""]},"WORC.classification.crossval":{LOO_cross_validation:[2,1,1,""],crossval:[2,1,1,""],nocrossval:[2,1,1,""],random_split_cross_validation:[2,1,1,""],test_RS_Ensemble:[2,1,1,""]},"WORC.classification.estimators":{RankedSVM:[2,2,1,""]},"WORC.classification.estimators.RankedSVM":{__init__:[2,4,1,""],__module__:[2,3,1,""],fit:[2,4,1,""],predict:[2,4,1,""],predict_proba:[2,4,1,""]},"WORC.classification.fitandscore":{delete_cc_para:[2,1,1,""],delete_nonestimator_parameters:[2,1,1,""],fit_and_score:[2,1,1,""],replacenan:[2,1,1,""]},"WORC.classification.metrics":{ICC:[2,1,1,""],ICC_anova:[2,1,1,""],check_multimetric_scoring:[2,1,1,""],check_scoring:[2,1,1,""],f1_weighted_predictproba:[2,1,1,""],multi_class_auc:[2,1,1,""],multi_class_auc_score:[2,1,1,""],pairwise_auc:[2,1,1,""],performance_multilabel:[2,1,1,""],performance_singlelabel:[2,1,1,""]},"WORC.classification.parameter_optimization":{random_search_parameters:[2,1,1,""]},"WORC.classification.trainclassifier":{add_parameters_to_grid:[2,1,1,""],trainclassifier:[2,1,1,""]},"WORC.detectors":{detectors:[4,0,0,"-"]},"WORC.detectors.detectors":{AbstractDetector:[4,2,1,""],BigrClusterDetector:[4,2,1,""],CartesiusClusterDetector:[4,2,1,""],CsvDetector:[4,2,1,""],DebugDetector:[4,2,1,""],HostnameDetector:[4,2,1,""],LinuxDetector:[4,2,1,""],WORCDirectoryDetector:[4,2,1,""]},"WORC.detectors.detectors.AbstractDetector":{__abstractmethods__:[4,3,1,""],__dict__:[4,3,1,""],__module__:[4,3,1,""],__weakref__:[4,3,1,""],do_detection:[4,4,1,""]},"WORC.detectors.detectors.BigrClusterDetector":{__abstractmethods__:[4,3,1,""],__module__:[4,3,1,""]},"WORC.detectors.detectors.CartesiusClusterDetector":{__abstractmethods__:[4,3,1,""],__module__:[4,3,1,""]},"WORC.detectors.detectors.CsvDetector":{__abstractmethods__:[4,3,1,""],__init__:[4,4,1,""],__module__:[4,3,1,""]},"WORC.detectors.detectors.DebugDetector":{__abstractmethods__:[4,3,1,""],__module__:[4,3,1,""]},"WORC.detectors.detectors.HostnameDetector":{__abstractmethods__:[4,3,1,""],__init__:[4,4,1,""],__module__:[4,3,1,""]},"WORC.detectors.detectors.LinuxDetector":{__abstractmethods__:[4,3,1,""],__module__:[4,3,1,""]},"WORC.detectors.detectors.WORCDirectoryDetector":{__abstractmethods__:[4,3,1,""],__module__:[4,3,1,""]},"WORC.exampledata":{create_example_data:[5,0,0,"-"],datadownloader:[5,0,0,"-"]},"WORC.exampledata.create_example_data":{create_random_features:[5,1,1,""]},"WORC.exampledata.datadownloader":{download_HeadAndNeck:[5,1,1,""],download_project:[5,1,1,""],download_subject:[5,1,1,""]},"WORC.facade":{basicworc:[6,0,0,"-"],simpleworc:[6,0,0,"-"]},"WORC.facade.basicworc":{BasicWORC:[6,2,1,""]},"WORC.facade.basicworc.BasicWORC":{__init__:[6,4,1,""],__module__:[6,3,1,""],execute:[6,4,1,""]},"WORC.facade.helpers":{configbuilder:[7,0,0,"-"],exceptions:[7,0,0,"-"],processing:[7,0,0,"-"]},"WORC.facade.helpers.configbuilder":{ConfigBuilder:[7,2,1,""]},"WORC.facade.helpers.configbuilder.ConfigBuilder":{__dict__:[7,3,1,""],__init__:[7,4,1,""],__module__:[7,3,1,""],__weakref__:[7,3,1,""],build_config:[7,4,1,""],coarse_overrides:[7,4,1,""],custom_config_overrides:[7,4,1,""],estimator_scoring_overrides:[7,4,1,""],fullprint:[7,4,1,""]},"WORC.facade.helpers.exceptions":{InvalidCsvFileException:[7,5,1,""],InvalidOrderException:[7,5,1,""],NoFeaturesFoundException:[7,5,1,""],NoImagesFoundException:[7,5,1,""],NoMasksFoundException:[7,5,1,""],NoSegmentationsFoundException:[7,5,1,""],PathNotFoundException:[7,5,1,""]},"WORC.facade.helpers.exceptions.InvalidCsvFileException":{__init__:[7,4,1,""],__module__:[7,3,1,""],__weakref__:[7,3,1,""]},"WORC.facade.helpers.exceptions.InvalidOrderException":{__init__:[7,4,1,""],__module__:[7,3,1,""],__weakref__:[7,3,1,""]},"WORC.facade.helpers.exceptions.NoFeaturesFoundException":{__init__:[7,4,1,""],__module__:[7,3,1,""],__weakref__:[7,3,1,""]},"WORC.facade.helpers.exceptions.NoImagesFoundException":{__init__:[7,4,1,""],__module__:[7,3,1,""],__weakref__:[7,3,1,""]},"WORC.facade.helpers.exceptions.NoMasksFoundException":{__init__:[7,4,1,""],__module__:[7,3,1,""],__weakref__:[7,3,1,""]},"WORC.facade.helpers.exceptions.NoSegmentationsFoundException":{__init__:[7,4,1,""],__module__:[7,3,1,""],__weakref__:[7,3,1,""]},"WORC.facade.helpers.exceptions.PathNotFoundException":{__init__:[7,4,1,""],__module__:[7,3,1,""],__weakref__:[7,3,1,""]},"WORC.facade.helpers.processing":{convert_radiomix_features:[7,1,1,""]},"WORC.facade.simpleworc":{SimpleWORC:[6,2,1,""]},"WORC.facade.simpleworc.SimpleWORC":{__dict__:[6,3,1,""],__init__:[6,4,1,""],__module__:[6,3,1,""],__weakref__:[6,3,1,""],add_config_overrides:[6,4,1,""],add_evaluation:[6,4,1,""],binary_classification:[6,4,1,""],count_num_subjects:[6,4,1,""],execute:[6,4,1,""],features_from_radiomix_xlsx:[6,4,1,""],features_from_this_directory:[6,4,1,""],images_from_this_directory:[6,4,1,""],labels_from_this_file:[6,4,1,""],masks_from_this_directory:[6,4,1,""],multiclass_classification:[6,4,1,""],predict_labels:[6,4,1,""],regression:[6,4,1,""],segmentations_from_this_directory:[6,4,1,""],semantics_from_this_file:[6,4,1,""],set_fixed_splits:[6,4,1,""],set_multicore_execution:[6,4,1,""],set_tmpdir:[6,4,1,""],survival:[6,4,1,""]},"WORC.featureprocessing":{ComBat:[9,0,0,"-"],Decomposition:[9,0,0,"-"],FeatureConverter:[9,0,0,"-"],ICCThreshold:[9,0,0,"-"],Imputer:[9,0,0,"-"],OneHotEncoderWrapper:[9,0,0,"-"],Preprocessor:[9,0,0,"-"],Relief:[9,0,0,"-"],Scalers:[9,0,0,"-"],SelectGroups:[9,0,0,"-"],SelectIndividuals:[9,0,0,"-"],StatisticalTestFeatures:[9,0,0,"-"],StatisticalTestThreshold:[9,0,0,"-"],VarianceThreshold:[9,0,0,"-"]},"WORC.featureprocessing.ComBat":{ComBat:[9,1,1,""],ComBatMatlab:[9,1,1,""],ComBatPython:[9,1,1,""],Synthetictest:[9,1,1,""]},"WORC.featureprocessing.Decomposition":{Decomposition:[9,1,1,""]},"WORC.featureprocessing.FeatureConverter":{FeatureConverter:[9,1,1,""],convert_PREDICT:[9,1,1,""],convert_pyradiomics:[9,1,1,""],convert_pyradiomics_featurevector:[9,1,1,""]},"WORC.featureprocessing.ICCThreshold":{ICCThreshold:[9,2,1,""],convert_features_ICC_threshold:[9,1,1,""]},"WORC.featureprocessing.ICCThreshold.ICCThreshold":{__abstractmethods__:[9,3,1,""],__init__:[9,4,1,""],__module__:[9,3,1,""],fit:[9,4,1,""],transform:[9,4,1,""]},"WORC.featureprocessing.Imputer":{Imputer:[9,2,1,""]},"WORC.featureprocessing.Imputer.Imputer":{__dict__:[9,3,1,""],__init__:[9,4,1,""],__module__:[9,3,1,""],__weakref__:[9,3,1,""],fit:[9,4,1,""],transform:[9,4,1,""]},"WORC.featureprocessing.OneHotEncoderWrapper":{OneHotEncoderWrapper:[9,2,1,""],test:[9,1,1,""]},"WORC.featureprocessing.OneHotEncoderWrapper.OneHotEncoderWrapper":{__dict__:[9,3,1,""],__init__:[9,4,1,""],__module__:[9,3,1,""],__weakref__:[9,3,1,""],fit:[9,4,1,""],transform:[9,4,1,""]},"WORC.featureprocessing.Preprocessor":{Preprocessor:[9,2,1,""]},"WORC.featureprocessing.Preprocessor.Preprocessor":{__dict__:[9,3,1,""],__init__:[9,4,1,""],__module__:[9,3,1,""],__weakref__:[9,3,1,""],fit:[9,4,1,""],transform:[9,4,1,""]},"WORC.featureprocessing.Relief":{SelectMulticlassRelief:[9,2,1,""]},"WORC.featureprocessing.Relief.SelectMulticlassRelief":{__abstractmethods__:[9,3,1,""],__init__:[9,4,1,""],__module__:[9,3,1,""],fit:[9,4,1,""],multi_class_relief:[9,4,1,""],single_class_relief:[9,4,1,""],transform:[9,4,1,""]},"WORC.featureprocessing.Scalers":{LogStandardScaler:[9,2,1,""],RobustStandardScaler:[9,2,1,""],WORCScaler:[9,2,1,""],test:[9,1,1,""]},"WORC.featureprocessing.Scalers.LogStandardScaler":{__module__:[9,3,1,""],fit:[9,4,1,""]},"WORC.featureprocessing.Scalers.RobustStandardScaler":{__module__:[9,3,1,""],fit:[9,4,1,""]},"WORC.featureprocessing.Scalers.WORCScaler":{__init__:[9,4,1,""],__module__:[9,3,1,""],fit:[9,4,1,""],transform:[9,4,1,""]},"WORC.featureprocessing.SelectGroups":{SelectGroups:[9,2,1,""]},"WORC.featureprocessing.SelectGroups.SelectGroups":{__abstractmethods__:[9,3,1,""],__init__:[9,4,1,""],__module__:[9,3,1,""],fit:[9,4,1,""],transform:[9,4,1,""]},"WORC.featureprocessing.SelectIndividuals":{SelectIndividuals:[9,2,1,""]},"WORC.featureprocessing.SelectIndividuals.SelectIndividuals":{__abstractmethods__:[9,3,1,""],__init__:[9,4,1,""],__module__:[9,3,1,""],fit:[9,4,1,""],transform:[9,4,1,""]},"WORC.featureprocessing.StatisticalTestFeatures":{StatisticalTestFeatures:[9,1,1,""]},"WORC.featureprocessing.StatisticalTestThreshold":{StatisticalTestThreshold:[9,2,1,""]},"WORC.featureprocessing.StatisticalTestThreshold.StatisticalTestThreshold":{__abstractmethods__:[9,3,1,""],__init__:[9,4,1,""],__module__:[9,3,1,""],fit:[9,4,1,""],transform:[9,4,1,""]},"WORC.featureprocessing.VarianceThreshold":{VarianceThresholdMean:[9,2,1,""],selfeat_variance:[9,1,1,""]},"WORC.featureprocessing.VarianceThreshold.VarianceThresholdMean":{__abstractmethods__:[9,3,1,""],__init__:[9,4,1,""],__module__:[9,3,1,""],fit:[9,4,1,""],transform:[9,4,1,""]},"WORC.plotting":{compute_CI:[10,0,0,"-"],linstretch:[10,0,0,"-"],plot_ROC:[10,0,0,"-"],plot_barchart:[10,0,0,"-"],plot_boxplot_features:[10,0,0,"-"],plot_boxplot_performance:[10,0,0,"-"],plot_errors:[10,0,0,"-"],plot_estimator_performance:[10,0,0,"-"],plot_hyperparameters:[10,0,0,"-"],plot_images:[10,0,0,"-"],plot_pvalues_features:[10,0,0,"-"],plot_ranked_scores:[10,0,0,"-"],plotminmaxresponse:[10,0,0,"-"],scatterplot:[10,0,0,"-"]},"WORC.plotting.compute_CI":{compute_confidence:[10,1,1,""],compute_confidence_bootstrap:[10,1,1,""],compute_confidence_logit:[10,1,1,""]},"WORC.plotting.linstretch":{linstretch:[10,1,1,""]},"WORC.plotting.plot_ROC":{curve_thresholding:[10,1,1,""],main:[10,1,1,""],plot_PRC_CIc:[10,1,1,""],plot_ROC:[10,1,1,""],plot_ROC_CIc:[10,1,1,""],plot_single_PRC:[10,1,1,""],plot_single_ROC:[10,1,1,""]},"WORC.plotting.plot_barchart":{count_parameters:[10,1,1,""],main:[10,1,1,""],paracheck:[10,1,1,""],plot_barchart:[10,1,1,""],plot_bars:[10,1,1,""]},"WORC.plotting.plot_boxplot_features":{generate_feature_boxplots:[10,1,1,""],plot_boxplot_features:[10,1,1,""]},"WORC.plotting.plot_boxplot_performance":{generate_performance_boxplots:[10,1,1,""],test:[10,1,1,""]},"WORC.plotting.plot_errors":{plot_errors:[10,1,1,""]},"WORC.plotting.plot_estimator_performance":{combine_multiple_estimators:[10,1,1,""],compute_statistics:[10,1,1,""],fit_thresholds:[10,1,1,""],main:[10,1,1,""],plot_estimator_performance:[10,1,1,""]},"WORC.plotting.plot_hyperparameters":{plot_hyperparameters:[10,1,1,""]},"WORC.plotting.plot_images":{bbox_2D:[10,1,1,""],extract_boundary:[10,1,1,""],plot_im_and_overlay:[10,1,1,""],slicer:[10,1,1,""]},"WORC.plotting.plot_pvalues_features":{manhattan_importance:[10,1,1,""]},"WORC.plotting.plot_ranked_scores":{example:[10,1,1,""],flatten_object:[10,1,1,""],main:[10,1,1,""],plot_ranked_images:[10,1,1,""],plot_ranked_percentages:[10,1,1,""],plot_ranked_posteriors:[10,1,1,""],plot_ranked_scores:[10,1,1,""]},"WORC.plotting.plotminmaxresponse":{main:[10,1,1,""]},"WORC.plotting.scatterplot":{main:[10,1,1,""],make_scatterplot:[10,1,1,""]},"WORC.processing":{ExtractNLargestBlobsn:[11,0,0,"-"],classes:[11,0,0,"-"],helpers:[11,0,0,"-"],label_processing:[11,0,0,"-"],preprocessing:[11,0,0,"-"],segmentix:[11,0,0,"-"]},"WORC.processing.ExtractNLargestBlobsn":{ExtractNLargestBlobsn:[11,1,1,""]},"WORC.processing.classes":{"switch":[11,2,1,""]},"WORC.processing.classes.switch":{__dict__:[11,3,1,""],__init__:[11,4,1,""],__iter__:[11,4,1,""],__module__:[11,3,1,""],__weakref__:[11,3,1,""],match:[11,4,1,""]},"WORC.processing.helpers":{check_image_orientation:[11,1,1,""],resample_image:[11,1,1,""],transpose_image:[11,1,1,""]},"WORC.processing.label_processing":{findlabeldata:[11,1,1,""],load_config_XNAT:[11,1,1,""],load_label_XNAT:[11,1,1,""],load_label_csv:[11,1,1,""],load_label_txt:[11,1,1,""],load_labels:[11,1,1,""]},"WORC.processing.preprocessing":{bias_correct_image:[11,1,1,""],clip_image:[11,1,1,""],normalize_image:[11,1,1,""],preprocess:[11,1,1,""]},"WORC.processing.segmentix":{dilate_contour:[11,1,1,""],get_ring:[11,1,1,""],mask_contour:[11,1,1,""],segmentix:[11,1,1,""]},"WORC.resources":{fastr_tools:[14,0,0,"-"]},"WORC.resources.fastr_tests":{CalcFeatures_test:[13,0,0,"-"],elastix_test:[13,0,0,"-"],segmentix_test:[13,0,0,"-"]},"WORC.resources.fastr_tests.CalcFeatures_test":{create_network:[13,1,1,""],main:[13,1,1,""],sink_data:[13,1,1,""],source_data:[13,1,1,""]},"WORC.resources.fastr_tests.elastix_test":{create_network:[13,1,1,""],main:[13,1,1,""],sink_data:[13,1,1,""],source_data:[13,1,1,""]},"WORC.resources.fastr_tests.segmentix_test":{create_network:[13,1,1,""],main:[13,1,1,""],sink_data:[13,1,1,""],source_data:[13,1,1,""]},"WORC.statistics":{delong:[15,0,0,"-"]},"WORC.statistics.delong":{calc_pvalue:[15,1,1,""],compute_ground_truth_statistics:[15,1,1,""],compute_midrank:[15,1,1,""],compute_midrank_weight:[15,1,1,""],delong_roc_test:[15,1,1,""],delong_roc_variance:[15,1,1,""],fastDeLong:[15,1,1,""]},"WORC.tests":{WORCTutorialSimple_travis_multiclass:[16,0,0,"-"],WORCTutorialSimple_travis_regression:[16,0,0,"-"],test_combat:[16,0,0,"-"],test_helpers:[16,0,0,"-"],test_iccthreshold:[16,0,0,"-"],test_plot_errors:[16,0,0,"-"],test_validators:[16,0,0,"-"]},"WORC.tests.WORCTutorialSimple_travis_multiclass":{main:[16,1,1,""]},"WORC.tests.WORCTutorialSimple_travis_regression":{main:[16,1,1,""]},"WORC.tests.test_combat":{test_combat:[16,1,1,""],test_combat_fastr:[16,1,1,""]},"WORC.tests.test_helpers":{find_exampledatadir:[16,1,1,""],find_testdatadir:[16,1,1,""]},"WORC.tests.test_iccthreshold":{test_iccthreshold:[16,1,1,""]},"WORC.tests.test_plot_errors":{test_plot_errors:[16,1,1,""]},"WORC.tests.test_validators":{test_invalidlabelsvalidator_columnsubstring:[16,1,1,""],test_invalidlabelsvalidator_patientcolumn:[16,1,1,""],test_invalidlabelsvalidator_patientsubstring:[16,1,1,""],test_invalidlabelsvalidator_validconfig:[16,1,1,""]},"WORC.tools":{Elastix:[17,0,0,"-"],Evaluate:[17,0,0,"-"],Inference:[17,0,0,"-"],Slicer:[17,0,0,"-"],Transformix:[17,0,0,"-"],createfixedsplits:[17,0,0,"-"]},"WORC.tools.Elastix":{Elastix:[17,2,1,""]},"WORC.tools.Elastix.Elastix":{__dict__:[17,3,1,""],__init__:[17,4,1,""],__module__:[17,3,1,""],__weakref__:[17,3,1,""],addchangeorder:[17,4,1,""],create_bbox:[17,4,1,""],create_network:[17,4,1,""],execute:[17,4,1,""],getparametermap:[17,4,1,""]},"WORC.tools.Evaluate":{Evaluate:[17,2,1,""]},"WORC.tools.Evaluate.Evaluate":{__dict__:[17,3,1,""],__init__:[17,4,1,""],__module__:[17,3,1,""],__weakref__:[17,3,1,""],create_links_Addon:[17,4,1,""],create_links_Standalone:[17,4,1,""],create_network:[17,4,1,""],execute:[17,4,1,""],set:[17,4,1,""]},"WORC.tools.Inference":{Inference:[17,2,1,""]},"WORC.tools.Inference.Inference":{__dict__:[17,3,1,""],__init__:[17,4,1,""],__module__:[17,3,1,""],__weakref__:[17,3,1,""],create_network:[17,4,1,""]},"WORC.tools.Slicer":{Slicer:[17,2,1,""]},"WORC.tools.Slicer.Slicer":{__dict__:[17,3,1,""],__init__:[17,4,1,""],__module__:[17,3,1,""],__weakref__:[17,3,1,""],create_network:[17,4,1,""],execute:[17,4,1,""],set:[17,4,1,""]},"WORC.tools.Transformix":{Transformix:[17,2,1,""]},"WORC.tools.Transformix.Transformix":{__dict__:[17,3,1,""],__init__:[17,4,1,""],__module__:[17,3,1,""],__weakref__:[17,3,1,""],create_network:[17,4,1,""],execute:[17,4,1,""]},"WORC.tools.createfixedsplits":{createfixedsplits:[17,1,1,""]},"WORC.validators":{preflightcheck:[18,0,0,"-"]},"WORC.validators.preflightcheck":{AbstractValidator:[18,2,1,""],EvaluateValidator:[18,2,1,""],InvalidLabelsValidator:[18,2,1,""],MinSubjectsValidator:[18,2,1,""],SamplesWarning:[18,2,1,""],SimpleValidator:[18,2,1,""],ValidatorsFactory:[18,2,1,""]},"WORC.validators.preflightcheck.AbstractValidator":{__abstractmethods__:[18,3,1,""],__dict__:[18,3,1,""],__module__:[18,3,1,""],__weakref__:[18,3,1,""],do_validation:[18,4,1,""]},"WORC.validators.preflightcheck.EvaluateValidator":{__abstractmethods__:[18,3,1,""],__module__:[18,3,1,""]},"WORC.validators.preflightcheck.InvalidLabelsValidator":{__abstractmethods__:[18,3,1,""],__module__:[18,3,1,""]},"WORC.validators.preflightcheck.MinSubjectsValidator":{__abstractmethods__:[18,3,1,""],__module__:[18,3,1,""]},"WORC.validators.preflightcheck.SamplesWarning":{__abstractmethods__:[18,3,1,""],__module__:[18,3,1,""]},"WORC.validators.preflightcheck.SimpleValidator":{__abstractmethods__:[18,3,1,""],__module__:[18,3,1,""]},"WORC.validators.preflightcheck.ValidatorsFactory":{__dict__:[18,3,1,""],__module__:[18,3,1,""],__weakref__:[18,3,1,""],factor_validators:[18,6,1,""]},WORC:{WORC:[0,0,0,"-"],__init__:[0,0,0,"-"],addexceptions:[0,0,0,"-"],classification:[2,0,0,"-"],facade:[6,0,0,"-"],featureprocessing:[9,0,0,"-"],plotting:[10,0,0,"-"]}},objnames:{"0":["py","module","Python module"],"1":["py","function","Python function"],"2":["py","class","Python class"],"3":["py","attribute","Python attribute"],"4":["py","method","Python method"],"5":["py","exception","Python exception"],"6":["py","staticmethod","Python static method"]},objtypes:{"0":"py:module","1":"py:function","2":"py:class","3":"py:attribute","4":"py:method","5":"py:exception","6":"py:staticmethod"},terms:{"0284186x":9,"06875v1":9,"0a1":66,"0rc1":59,"105741d":59,"1st":2,"1x1x1":[50,60,62],"22nd":70,"2nd":[2,66],"5th":9,"95th":9,"95varianc":[33,34,62],"98nd":66,"boolean":[0,1,2,6,9,10,11,19,25,31,33,39,43,47,51,52,57,59,61,62],"case":[2,11,24,61,62,64,66,70],"catch":[0,61],"class":[0,2,4,6,7,9,15,17,18,59,61,64,70],"default":[0,1,2,6,9,10,11,17,19,21,22,23,25,27,28,29,31,33,35,37,39,41,43,45,47,49,51,53,55,57,60,61,62,64,65,66,69,70],"export":68,"final":[2,9,11,62,70],"float":[2,9,10,11,15,21,25,33,39,41,42,49,51,53,61,62,66],"function":[0,2,4,6,7,9,10,11,16,17,18,22,50,59,61,62,63,64,65,66,67,69,70],"gr\u00fcnhagen":59,"import":[2,9,34,59,61,62,68,70],"int":[2,9,11],"long":66,"new":[0,59,61,66,68],"return":[0,1,2,9,10,11,15,61,64],"short":66,"static":[18,42,62],"switch":[9,11,61],"throw":[61,66],"true":[0,2,5,6,9,10,11,21,26,29,32,33,37,38,40,41,43,44,48,49,50,51,55,57,58,60,62,69,70],"try":[2,60,68],"while":[2,11,40,61,62,66],Added:59,Adding:59,Age:69,And:9,Els:59,For:[0,2,6,9,22,42,48,59,60,61,62,63,64,65,66,68,69,70],IDs:[11,65],Not:[2,6,61,68],One:[2,54,61,62],PCs:[22,62],SVs:2,That:9,The:[0,1,2,6,9,10,11,15,26,34,46,59,60,61,62,63,64,65,66,67,68],Then:2,There:[61,69,70],These:[10,62,64,66,69,70],USING:59,Use:[2,6,19,20,22,27,28,31,32,47,48,53,54,61,62,66,69],Using:[59,68],Vos:59,Was:61,Will:6,With:59,__abstractmethods__:[2,4,9,18],__dict__:[0,2,4,6,7,9,11,17,18],__doc__:[0,2,4,6,7,9,11,17,18],__file__:69,__init__:[0,2,4,6,7,9,11,17],__iter__:[2,11],__len__:2,__module__:[0,2,4,6,7,9,11,17,18],__weakref__:[0,2,4,6,7,9,11,17,18],_abc_data:[4,18],_abc_impl:[4,18],_base:9,_cluster_config_overrid:7,_data:9,_debug_config_overrid:7,_format_result:2,_generate_detector_messag:[4,18],_is_detect:4,_set_and_validate_estim:6,_valid:[6,18],abbrevi:[22,62],abc:[4,18],about:66,abov:[2,9,60,61,62,66,68,69,70],absolut:61,abspath:69,abstractdetector:4,abstractvalid:18,accept:[2,39,61,62],accorad:2,accord:[2,9,10,66,69,70],accordingli:[60,69],account:[9,10,70],accur:[2,4,7,9,11,17],accuraci:[2,10,70],acquisit:68,across:2,act:62,actual:[0,2,6,30,59,60,61,62,63,64,68,70],adaboost:[22,61,62],adaboost_learning_r:[21,22,62],adaboost_n_estim:[21,22,62],adaboostclassifi:[21,62],adaboostregressor:[21,62],adapt:[59,68],adasyn:[2,53,61,62],add:[0,2,6,9,17,61,64,65,66,67,69,70],add_combat:0,add_config_overrid:6,add_elastix:0,add_elastix_sourcesandsink:0,add_evalu:[0,6,69,70],add_feature_calcul:[0,64],add_parameters_to_grid:2,add_preprocess:0,add_segmentix:0,add_tool:0,addchangeord:17,added:[9,17,24,61,62,64,70],addexcept:59,addinf:61,adding:[2,17,62,64,69,70],addit:[0,6,38,59,61,62,66,69,70],addition:[1,9,10,61,62,70],address:59,adequ:64,adher:61,adjust:[2,10,61,62,70],adopt:[2,15,54,61,62],advanc:[59,69,70],advancedsampl:[0,59],advantag:62,advic:[52,60,62,64,69,70],affect:2,affin:17,after:[0,2,9,38,60,61,62,64,65,66,69,70],afterward:[6,9],again:[62,66,68,69],age:[41,62,66,70],agesex:10,aggreg:66,agument:11,aim:59,aka:70,alejandro:66,alex:66,algorithm:[2,15,60,61,62,68],align:70,all:[0,1,2,6,9,10,11,21,24,38,40,44,48,53,57,58,60,61,62,63,64,65,66,68,69,70],allign:70,allow:[2,6,61,66,67],allow_non:2,along:[9,68],alpha:[2,10],alpha_new:2,alpha_old:2,alreadi:[60,62,68,70],als:70,also:[0,2,6,9,34,54,59,60,61,62,64,65,66,68,69,70],alter:[2,11,61,62,66],altern:70,although:68,alwai:[2,9,61,68,69,70],among:[2,9,10,59,62],amount:[66,68],anaconda:[65,69],analys:69,analysi:[34,59,62,66,70],analyticsvidhya:62,angl:[42,62,66],angu:59,angular:66,ani:[2,9,10,21,39,48,61,62,65,66,68,69,70],annual:59,anoth:[11,60,68,70],anova:2,any_structur:2,anymor:61,anyth:68,anywai:9,apach:59,api:[54,60,62],appear:66,append:[61,62,70],appendix:2,appli:[0,2,6,9,11,38,50,60,61,62,66,68],applic:[11,59,66,68],approach:[9,59,62,68],appropri:0,arbitrari:66,area:[15,66,70],arg:[1,2,4,11,15,18],argmax:10,argu:66,argument:[0,1,2,11,61,64,65],arif:59,around:[2,6,17,56,60,62,64,70],arrai:[1,2,9,10,11,15,59],artefact:66,articl:[15,59,66],arxiv:[9,59],asm:66,aspect:66,assertionerror:0,assess:[6,9,61],assign:[2,40,42,62],assist:[59,66],associ:2,assum:[2,9,50,60,62,65,68,69,70],assumesameimageandmaskmetadata:[11,37,38,62],assumpt:[2,38,62,70],attribut:[0,2,4,6,7,9,11,17,18,59,61],atyp:70,auc:[2,15,70],author:15,auto:[2,53,62],autom:59,automat:[0,6,11,40,59,60,61,62,66,68,69],avail:[2,6,61,63,68],averag:[10,61],average_precision_weight:[39,62],avoid:[2,60,66],awai:66,axes:66,axi:[9,50,62,66],axial:[11,49,50,51,56,60,61,62,66],back:[61,65],backend:[38,61,62],backward:61,balanc:70,band:[6,70],bangma:59,barchart:[10,61,70],base:[0,2,4,5,6,7,9,10,11,17,18,34,50,59,61,62,66,70],baseestim:[2,9],baselin:68,basesearchcv:2,basesearchcvfastr:2,basesearchcvjoblib:2,basestr:6,basi:70,basic:[64,66,68,70],basicworc:[0,59,61,69,70],batch:[9,23,24,60,62],bay:[24,62],bbox_2d:10,bca:70,been:[0,9,10,59,66,68,69],befor:[0,2,6,9,42,60,61,62,65,66,68,69],beforehand:66,begin:[59,61],beginn:59,behavior:2,behaviour:61,being:[15,50,62],belong:[0,2,9],below:[0,2,34,48,60,62,66,68,69,70],benefit:[60,66,68],bengio:70,benign:59,bent:59,berlin:66,besid:[0,59,62,70],best:[2,10,61,62,63,68],best_estim:2,best_estimator_:2,best_index_:2,best_params_:2,best_score_:2,beta:2,better:61,between:[2,9,17,21,22,34,42,59,61,62,66],bia:[2,11,50,60,61,62],bias_correct_imag:11,biascorrect:[49,50,62],biascorrection_mask:[49,50,62],big:61,bigr:[6,40,62,69],bigr_erasmusmc:2,bigrclusterdetector:4,bin:[52,59,62,64],binari:[2,6,9,10,11,59,61,69],binary_classif:[0,6,17,69],binaryimag:11,bincount:[51,52,62],binwidth:[51,52,62],bio:59,biomark:[59,66,68],biomed:59,bit:61,bitbucket:2,bitwise_xor:61,black:59,blazev:59,blob:[11,56,60,62,64],block:69,blog:62,bme:59,bmia:69,boht:66,bonferonni:9,book:59,bool:2,boolean_uniform:2,boost:[22,61,62],boostrap:61,bootstrap:[3,10,20,59,61,70],bootstrap_metr:10,bootstrap_n:10,border:60,borderlinesmot:[2,53,62],both:[2,10,59,60,61,62,64,66,68,70],bound:[11,17],boundari:[9,10,11,34,42,62],box:[17,59,62],boxplot:[10,61],braband:59,braf:59,branch:[0,22,62],breviti:69,british:59,broad:66,brought:68,bug:61,bugfix:61,buggi:61,build:[0,17,59,61,68,69,70],build_config:7,build_train:0,built:69,buisman:59,bulletin:9,busy:66,button:59,c_valu:2,cache_s:2,cad:2,caddementia:2,calc_pvalu:15,calcfeat_nod:0,calcfeatur:[37,61,62],calcfeatures_test:[0,12],calcul:[0,2,9,10,38,62,64],call:[2,61,64,66,69,70],callabl:2,can:[0,2,6,9,10,11,17,34,38,42,44,50,59,60,61,62,64,65,66,68,69,70],cancer:[59,66],candid:2,cannot:[2,59,60,61],captur:60,carcinoma:59,cardin:61,cartesiu:[6,69],cartesiusclusterdetector:4,caruana:[2,10],cash:[62,68],cast:61,castillo:59,categor:[9,61],categori:70,caught:6,center:[59,66],centr:66,certain:[2,6,17,60,61,62,66,70],cf_pyradiom:[37,62],challeg:2,challeng:[2,70],chang:[6,59,60,62,64,66,69],changelog:59,chapter:[6,59,60,62,63,65,66,67,69,70],characterist:[10,15,70],check:[2,6,11,48,50,60,61,62,64,70],check_image_orient:11,check_multimetric_scor:2,check_scor:2,checkorient:[49,50,62],checkspac:[49,50,62],chi2:61,child:[22,62],choic:[2,59,68],choos:[2,50,61,62],chosen:[2,62,66],chunk:2,chunksdict:2,circular:66,class_i:2,class_j:2,class_weight:2,classfic:[40,62],classif:[0,3,6,22,46,61,64,66,69,70],classifi:[0,2,10,21,22,32,59,61,62,65,70],classifier_data:2,classifiermixin:2,classpi:2,clean:[54,61,62],clf:2,clinic:68,clip:[11,49,50,60,61,62],clip_imag:11,clipping_rang:[49,50,62],clone:69,closest:2,cluster:[2,6,22,40,61,62,68,69],cnb_alpha:[21,22,62],coars:[6,66,69],coarse_overrid:7,code:[60,62,69],coef0:2,coeffici:[2,9,70],col:[22,62],coliag:[41,42,58,62],coliage_featur:[9,57,58,62],collabor:59,colleagu:68,color:10,colorect:59,column:[2,6,9,59,66,70],com:[6,9,15,38,59,62,64,65,66,69,70],combat:[0,3,16,24,37,38,59,61],combatharmon:[9,38,62],combatmatlab:9,combatpython:9,combin:[1,2,9,10,24,31,32,59,61,62,63,66,68,70],combine_featur:1,combine_method:[1,31,32,62],combine_multiple_estim:10,comma:[2,9,21,23,35,36,41,62],command:[0,2,9,17,59,61,62,64,65,68,69],common:[2,6],commonli:66,commun:69,compact:66,compar:[15,68],comparison:[59,66],compat:[1,7,9,11,60,61,64],complementari:66,complementnb:[22,62],complementnd:[21,62],complet:[61,62,69,70],complex:[66,70],compon:[9,17,34,60,62,68,70],comprehens:[60,63,66],comput:[0,2,6,9,10,15,16,42,52,59,60,61,62,66,68,69,70],compute_ci:[0,59],compute_confid:10,compute_confidence_bootstrap:10,compute_confidence_logit:10,compute_ground_truth_statist:15,compute_midrank:15,compute_midrank_weight:15,compute_statist:10,concept:[59,68],concern:68,concord:70,conda:65,condit:65,conduct:[2,61,70],confer:[59,66,70],conffid:61,confid:[6,10,61,70],config:[0,1,2,6,7,9,10,11,17,22,34,60,61,62,63,64,66,69,70],config_file_path:[1,11],config_io_classifi:[0,59,64],config_io_combat:[0,59],config_io_pyradiom:[0,59],config_preprocess:[0,59],config_segmentix:[0,59],config_worc:[0,59],configbuild:[0,6,61],configpars:[0,11,62],configur:[0,1,2,6,9,59,60,61,64,65,67,69,70],confipars:1,congress:59,congruenc:66,connect:59,consist:[2,39,40,62,69,70],consol:7,constant:[9,43,62,68],construct:[2,6,10,59,69],construct_classifi:[0,59],construct_svm:2,consumpt:2,contain:[0,1,2,6,9,10,11,36,61,62,66,69,70],containingfor:2,content:[7,11,59,66],continu:[2,61,69],contour:[10,11,56,60,62],contrast:[2,66],contribut:59,control:2,converg:[10,61],convers:61,convert:[1,7,9,61,64,66],convert_config_pyradiom:1,convert_features_icc_threshold:9,convert_predict:9,convert_pyradiom:9,convert_pyradiomics_featurevector:9,convert_radiomix_featur:7,convex:66,copi:[0,2,9,11,38,59,60,61,62,64],copymetadata:0,core:[2,6,38,40,61,62,66,69],coron:[51,62],correct:[11,24,50,60,61,62,70],correctli:[10,61,65,70],correl:[9,15,66,68,70],correspond:[2,9,10,40,52,61,62,66,70],cost:2,could:[61,65,66,68],count:[6,52,62,66],count_num_subject:6,count_paramet:10,coupl:70,cours:70,covari:15,cox:70,cpu:2,crash:[59,61,69],creat:[0,2,5,6,10,17,61,62,66,68,69,70],creata:2,create_bbox:17,create_ensembl:[2,61],create_example_data:[0,59,70],create_links_addon:17,create_links_standalon:17,create_network:[13,17],create_param_grid:2,create_random_featur:5,create_sourc:62,createfixedsplit:[0,59],creation:[59,61,66],criteria:59,criterion:2,crop:68,cross:[0,2,10,17,26,38,40,61,62,70],cross_valid:[37,38,62],crossval:[0,59],crossval_typ:10,crossvalid:[3,59],csv:[6,9,10,61,69,70],csv_file_path:4,csv_out:9,csvdetector:4,ct001:0,ct002:0,cto:59,current:[0,2,9,11,26,32,50,59,60,61,62,65,68,70],curv:[6,10,15,61,70],curve_threshold:10,custom:[2,51,52,62],custom_config_overrid:7,cv_iter:2,cv_results_:2,cyan:10,dai:65,dat:9,data:[0,2,9,10,11,16,26,59,60,61,62,66,68,69],data_path:69,datadir:69,datadownload:[0,59,61,69],datafil:61,datafold:[5,69],datafram:[2,10],dataset:[0,2,6,30,38,40,59,60,61,62,68,69,70],datatyp:[61,64,67],datayp:61,dcm:11,deal:[60,61],debug:[10,38,59,61,62,69],debugdetector:4,decent:68,decid:[66,68],decision_funct:2,decision_function_shap:2,decod:66,decomposit:[0,6,59,61,70],decompositon:61,default_queu:65,default_scor:2,defaultconfig:[0,7,62,64,70],defin:[0,2,4,6,7,9,11,17,18,34,56,62,63,64,66,68,69,70],definit:[9,59,66],degre:[2,22,42,62,66],del:69,delai:2,delet:[2,59,61,64],delete_cc_para:2,delete_nonestimator_paramet:2,delong:[0,59],delong_roc_test:15,delong_roc_vari:15,demand:2,dementia:2,demo_param:2,demonst:2,den:59,depend:[0,2,10,59,61,65,68,70],deprec:61,depth:[22,62],der:59,describ:[0,2,63,66,67,70],descript:[2,9,20,22,24,26,28,30,32,34,36,38,40,42,44,46,48,50,52,54,56,58,60,62,64,66,69],descriptor:66,design:68,desmoid:59,despit:59,detail:[2,6,10,11,60,62,65,66,70],detect:[61,65,66],detector:[0,6,59,61,69],determin:[1,2,6,10,11,20,28,32,34,36,38,42,44,46,48,50,52,56,59,61,62,66,68,69,70],determinist:2,develop:[2,66,68],developp:61,deviat:[9,42,62,66],diagnosi:59,diagnost:59,diamet:66,dicom:[0,41,42,50,58,59,60,61,62,70],dicom_featur:[9,57,58,61,62],dicom_feature_label:[41,42,62,66],dicom_feature_tag:[41,42,62,66],dict:[0,1,2,9,11],dictionari:[0,1,2,6,10,11,61,62,70],did:[61,64,68,70],didn:61,differ:[2,10,11,15,59,60,61,68],differenti:59,difficult:68,difscal:9,digit:66,dilat:[11,50,55,56,60,61,62,70],dilate_contour:11,dilate_roi:11,dimens:66,dimension:68,direct:[61,66],directli:[6,66,68,69,70],directori:[0,6,62,69],dirnam:69,disabl:[52,61,62],disc:[50,56,62],discret:[42,62,66],discrete_uniform:2,discrimin:59,discuss:[60,66,70],dispatch:2,dissimilar:66,distanc:[9,34,42,62,66],distance_p:9,distinguish:[2,59,70],distribut:[2,61,64,69,70],distrubit:2,divers:68,divid:68,do_detect:4,do_test_rs_ensembl:2,do_valid:18,doc:64,docstr:70,doctest:2,document:[2,6,9,60,61,63,65,69,70],doe:[2,9,61,62,65,66],doi:9,doing:[2,62],don:69,done:[0,2,60,61,62,63,64,66,68,70],down:61,download:[61,69],download_headandneck:[5,69],download_project:5,download_subject:5,dpi:10,draw_network:70,drawback:66,drawn:[2,40,62],drmaa:[40,62],drmaaplugin:65,drop:61,drug:66,dti:61,dtrf:59,due:[2,61,68],dummi:61,dure:[2,40,61,62,65],dwarkas:59,e104:66,e107:66,each:[2,6,9,10,11,42,61,62,65,66,68,69,70],earlier:[66,69],easi:[59,68],easier:[61,68,70],easili:[61,62,68,69,70],echo:66,ecr:59,edg:[42,62,66],edit:[69,70],editelastixtransformfil:61,edwardo:2,effect:59,effici:[2,61,66],effort:68,efron:70,eigen:[21,62],either:[0,2,9,10,24,34,62,69,70],ejrad:[],elasticnet:[21,22,61,62],elasticnet_alpha:[21,22,62],elasticnet_l1_ratio:[21,22,62],elastix4:[37,62],elastix:[0,37,59,61,62,70],elastix_para:0,elastix_test:[0,12],electr:66,element:[9,34,50,62,70],elif:[65,69],ellip:66,ellipsi:2,ellipt:66,elong:66,els:[64,65],emb:64,embed:[60,61,63],emper:[24,62],emphasi:66,empir:70,emploi:2,empti:2,emptygraylevel:65,enabl:[2,6,52,62],encod:[2,48,62],end:[59,64],energi:66,engin:[2,59,68],enhanc:66,enough:2,ensembl:[2,3,10,17,28,40,59,61,68],ensemble_scor:10,ensur:0,enter:[2,11],entir:2,entri:59,entropi:66,environ:65,epsilon_insensit:[21,62],equal:[2,9,22,24,28,50,62,66],erasmu:68,error:[2,6,10,16,59,61,66,69,70],error_scor:2,especi:[2,38,59,61,62],establish:[59,66],estim:[0,6,7,10,17,21,22,28,34,40,59,61,62],estimator_input:2,estimator_scoring_overrid:7,estsiz:10,etc:[2,9,10,59],etcetera:69,european:59,eusomii:59,evalu:[0,2,3,6,10,30,40,59,61,69],evaluatevalid:18,even:66,everi:[38,62,68],everywher:64,exact:2,exampl:[0,2,6,10,11,15,16,17,48,59,61,62,65,66,68,69],example_stwstrategyhn:69,exampledata:[0,59,69,70],examplefil:69,excel:[66,70],except:[0,6,61],exclud:[9,24,32,34,62],excluded_featur:[23,24,62],exctract:66,exe:[23,62],execut:[0,2,6,16,17,21,22,24,59,61,62,64,68,69],execute_first:7,executionplugin:65,exhaust:2,exist:[17,61,68],exp:2,exp_uniform:2,expand:[10,61,66],expect:[68,69],expected_hostnam:4,experi:[2,6,16,59,61,66,70],experiment:[30,62],experiment_fold:69,experiment_nam:69,expert:66,explain:[34,62],explant:66,explicit:2,explor:2,explos:2,expon:[2,22,62],express:2,extens:[61,68,69],extrac:60,extract:[1,2,6,9,10,11,42,52,56,59,60,61,62,68,70],extract_boundari:10,extract_firstord:[51,52,62],extract_shap:[51,52,62],extractnlargestblobsn:[0,59],extractor:[51,52,62],extrat:11,f1_score:61,f1_weight:[2,6,39,62],f1_weighted_predictproba:[2,39,62],f6d255a45dd:62,facad:[0,7,59,61,69,70],facilit:[59,68],factor_valid:18,fail:61,fals:[1,2,5,9,10,11,17,19,21,22,25,29,31,37,39,41,44,47,49,50,51,55,57,59,62,69],familiar:68,fancyimput:9,faq:[59,61],fashion:69,fast:[2,15,59],fastdelong:15,fastr3:61,fastr:[0,2,6,17,21,22,40,59,61,62,64,65,69,70],fastr_plugin:[0,2,17,21,22,62],fastr_tempdir:[0,62],fastr_test:[0,12],fastr_tool:[0,12],fastrconfig:[0,59,62,70],fastrhom:62,fat:66,fator:2,fatsat:66,fault:61,feat:1,feat_in:9,feat_out:9,feat_out_0:59,feat_test:2,feat_train:2,featpreprocess:[3,59],featsel:[3,59],featur:[0,1,2,5,6,7,9,10,11,16,17,24,32,34,36,38,42,44,48,51,52,58,59,60,61,62,68,69],feature_fil:[6,69],feature_file_nam:6,feature_label:[2,9,10,69],feature_label_1:10,feature_label_2:10,feature_labels_tofit:[9,47,48,62],feature_select:[9,34,62],feature_set:9,feature_valu:[2,9,69],featurecalcul:[37,38,62,64],featureconvert:[0,59,64],featurefil:[1,10],featurefile_p1:69,featurenam:10,featureprocess:[0,59,64],features_:69,features_from_radiomix_xlsx:6,features_from_this_directori:[6,69],features_in:9,features_mod1_patient1:1,features_mod1_patient2:1,features_mod2_patient1:1,features_mod2_patient2:1,features_out:9,features_p1:69,features_test:70,features_test_in:9,features_test_out:9,features_train:70,features_train_in:9,features_train_out:9,featuresc:[3,59],featuresdatadir:69,featurevector:9,feel:[68,69],fellow:68,felt:68,fetur:[11,66],few:68,fewer:66,fibromatosi:59,fibrosi:59,fiduzi:59,field:[1,2,9,11,36,48,60,61,62,64,66,68,69],fig:10,figsiz:10,figur:[10,61,68],figwidth:10,fij:9,file1:[2,9],file2:[2,9],file3:[2,9],file:[0,1,2,5,6,9,10,11,46,59,60,61,62,64,66,69],file_io:[0,59,61],file_path:6,filenam:[10,11,65,70],filepath:[10,61],filesmatlabr2015bbinmatlab:[23,62],filesystem:61,fill:[56,60,62],fill_valu:9,fillhol:[55,56,62],filter:[42,59,62,68],finalbsplineinterpolationord:61,find:[2,16,59,61,63,65,68,69],find_exampledatadir:16,find_testdatadir:16,findlabeldata:11,first:[6,9,10,15,34,52,59,61,62,66,68,69,70],fit:[2,9,30,40,61,62,63,64,66,70],fit_and_scor:[2,63,64],fit_param:2,fit_threshold:10,fit_tim:2,fitandscor:[0,59,61,63,64],fitfailedwarn:2,fittd:2,fitted_workflow:2,five:[64,68],fix:[2,10,17,26,34,52,59,62,65,68,70],fixandscor:61,fixed_se:[2,25,26,62],fixed_splits_csv:6,fixedsplit:2,flag:61,flat:66,flatten:[10,61],flatten_object:10,fleiss:9,flexibl:[61,68],flip:[10,66],fluctuat:66,focu:70,focuss:70,fold:2,folder:[2,7,10,16,61,62,64,69,70],follow:[2,9,10,59,60,62,64,65,66,68,69,70],fontsiz:[9,10],force2d:[51,52,62],force2ddimens:[51,52,62],foremost:66,foresight:68,forest:[34,62],fork:65,form:66,format:[0,1,2,5,6,7,9,10,11,59,60,61,62,64,65,70],formula:2,forward:68,found:[2,59,61,62,68,69,70],foundat:59,four:68,fpr:10,fractal:[58,61,62],fractal_featur:[9,57,58,62],framework:[59,61,68],frangi:[42,62,66],free:69,freeli:70,frequenc:[42,62,66],frequent:9,from:[0,1,2,6,7,9,10,11,15,21,24,38,40,42,46,56,59,60,61,62,64,65,66,68,69,70],frozenset:[2,4,9,18],fulfil:2,full:[6,7,10,11,38,49,50,59,60,61,62,69],fulli:[6,59,61],fullprint:7,fun:68,function_bas:59,funtion:9,further:61,furthermor:66,futur:61,gabor:[42,58,59,61,62],gabor_angl:[41,42,62,66],gabor_frequ:[41,42,62,66],gamma:[2,22,62],garcia:2,gastrointestin:59,gather:10,gaussian:[52,59,62],gaussiannb:[21,62],gave:[2,61],gclm:[48,62,66],gener:[0,2,3,6,9,10,21,22,27,34,50,59,60,61,64,65,66,68,70],generalis:59,generaliz:59,generate_config:64,generate_feature_boxplot:10,generate_performance_boxplot:10,genet:[11,70],geometrytoler:[51,52,62],get:[2,10,11,59,68,69,70],get_r:11,getparametermap:17,gibhub:59,git:69,github:[1,2,6,9,10,11,15,38,59,62,64,65,69,70],give:[2,48,60,61,62,65,66,68,69,70],given:[0,2,6,9,10,40,42,59,61,62,64,66,69,70],glcm:[42,48,52,58,59,62,65],glcm_angl:[41,42,62,66],glcm_distanc:[41,42,62,66],glcm_level:[41,42,62,66],glcmm:66,gldm:[52,58,59,62,65],gldzm:[58,61,62],glob:[6,69],glrlm:[42,52,58,59,62,65],glszm:[42,52,58,59,62,65],gmean:[39,62],going:68,good:70,grade:59,grahpviz:61,grai:59,grand:2,graphviz:61,grayscal:[42,62],grid:[2,40,62],grid_scor:61,gridsearch:[22,62],gridsearchcv:2,gridsearchcvfastr:2,gridsearchcvjoblib:2,griethuysen:66,grlm:66,ground:[10,70],ground_truth:15,groundtruth:2,group:[2,9,34,61,62,66,68,70],groupsel:[2,64],groupwis:[2,61,66,70],groupwisesearch:[33,34,62],growth:59,gsout:2,guarante:2,guid:[2,59,62],guidelin:70,hack:65,had:[61,68],haibo:2,halton:2,haltonsampl:2,hand:68,handbook:59,handl:[9,61],handle_unknown:9,hanff:59,happen:66,harmon:[0,9,16,38,59,60,61,62],has:[0,2,6,9,50,59,62,65,66,68],have:[0,2,9,10,11,34,38,59,60,61,62,64,65,66,68,69,70],hdf5:[1,2,6,7,9,10,59,69,70],head:[69,70],header:[0,2,6,66,70],heidelberg:66,held:2,help:[2,4,7,9,11,17,61,70],helper:[0,6,59],henc:[2,6,9,10,60,61,62,64,66,68,70],hepatocellular:59,herder:59,here:[2,60,62,63,64,66,70],hf_mean:9,high:[59,66,68,69],higher:2,highest:2,highli:[2,68],highlight:[51,52,62],hing:[21,62],histogram:[2,41,42,58,59,62],histogram_featur:[9,57,58,62],histopatholog:59,histori:68,hofland:59,hold:[0,2],hole:[56,60,62],home:61,homogen:[22,62,66],hope:59,horribl:69,hospit:[23,62],host:59,hostnamedetector:4,hot:[48,62],hounsfield:62,how:[1,2,10,11,28,42,56,61,62,64,66,68,69,70],howev:[2,60,62,64,66,68,70],htm:62,html:[0,9,21,22,34,42,51,52,60,62],http:[0,2,6,9,15,21,22,34,38,42,51,52,54,59,60,62,64,65,69,70],huber:[21,62],hyper:[2,62],hyperoptim:[3,28,40,59,60,61],hyperparamat:2,hyperparamet:[2,10,40,61,62,63,66,68],hypothes:66,hypothesi:15,i_max:10,i_min:10,icc:[2,9,16,59,61,70],icc_anova:2,iccthreshold:[0,59],icctyp:[2,9],idea:[68,70],ident:2,identifi:[6,69],ids:[2,11],ieee:[2,15,59,66],ignor:[9,62],iid:2,iivarinen:66,illustr:68,imag:[0,2,6,10,11,17,38,42,50,52,59,61,62,68,69],image_featur:[2,9,10],image_features_test:2,image_features_train:2,image_file_nam:[6,69],image_mr:70,image_typ:[41,42,62],imagedatadir:69,imagefeatur:[3,59,66,70],imagefil:11,images1:70,images_from_this_directori:[6,69],images_test:70,images_train:[0,6,70],imagetyp:62,imaginary_label_1:69,imbalanc:[2,54,61,62],img2:10,img:[10,11],immedi:2,implement:[0,2,6,9,11,15,22,24,62,68,70],implicitli:68,imposs:2,improv:[2,66],imput:[0,2,3,44,59,61,64,68],imputat:2,incekara:59,includ:[0,2,6,11,28,32,60,61,62,64,66,68,69,70],incompat:[52,62],incorpor:61,incorrect:[50,61,62],incorrectli:[10,61,70],increas:[2,40,61,62],inde:66,independ:[68,70],index:[2,9,10,59,62,66,70],indexerror:[0,59],indic:[2,11],individu:2,ineffici:68,infer:[0,40,59,62,70],infinit:61,influenc:66,info:[6,62,65],inform:[2,9,10,38,59,62,64,66,69,70],informat:59,ini:[0,1,2,9,11,61,62,64],init:[9,64],init_adasyn:2,init_borderlinesmot:2,init_nearmiss:2,init_neighbourhoodcleaningrul:2,init_randomoversampl:2,init_randomundersampl:2,init_smot:2,init_smoteenn:2,init_smotetomek:2,initi:[0,2,4,6,7,9,11,17,61,66],inner:[42,60,62,66],input:[0,2,6,9,10,11,17,59,61,62,64,65,68],input_fil:[7,11],inputarrai:9,inset:61,insight:70,inspect:61,instal:[59,60,61,62],instanc:[0,2],instanti:2,instead:[2,52,60,61,62,66,69,70],integ:[2,6,9,10,11,19,21,25,27,28,33,37,39,40,41,42,43,44,49,51,52,53,55,59,61,62],integr:[59,61,68],intellig:66,intens:[11,50,52,60,62,66],inter:[2,9],interact:[6,59,61,69],interest:[6,66],interfac:2,intermed:10,intermedi:2,intermediatefacad:61,intern:[59,66,70],interpol:[11,51,52,62],interpret:[64,68],interquartil:66,interv:[6,10,61,70],intervent:[59,66],intra:[2,9],intraclass:[9,70],introduct:[59,69],introductori:68,invalidcsvfileexcept:7,invalidlabelsvalid:18,invalidorderexcept:7,invari:66,inverse_transform:2,involv:2,ioerror:0,iopars:[0,2,59,64],ioplugin:0,iri:2,is_empti:2,is_multimetr:2,is_train:6,isbi:59,isi:70,isn:61,issu:[59,61,65,68,69,70],item:[0,2,9,69],iter:[2,10,20,22,38,40,61,62,64,70],ith:2,itk:[0,11,61],itkimag:10,its:[2,68],itself:[66,68,70],jacob:66,jalv:59,jfortin1:[9,38,62],jiaj:66,job:[2,6,40,61,62],joblib:[2,22,38,61,62],joblib_backend:[37,38,62],joblib_ncor:[37,38,62],join:69,joost:66,joseph:9,journal:[15,59,66],json:[2,11,61,69],jth:2,jukka:66,just:[10,61,64,69,70],k_neighbor:[2,53,54,62],kapsa:59,keep:[2,11,59,61,68],kei:[2,3,41,61,62,70],kept:9,kernel:[2,22,62,70],kessel:59,keyerror:0,kfold:2,kind:[61,68],klein:59,knn:[9,43,44,61,62],knnimput:61,know:62,knowledg:2,known:66,kovesi:66,kurtosi:66,kwarg:[2,4,18],label1:[45,62,70],label2:[45,62,70],label:[0,1,2,3,6,9,10,11,15,24,46,48,51,52,59,60,61,66,68,69],label_1_count:15,label_data:[2,10,11],label_data_test:2,label_data_train:2,label_fil:[2,10,11,17,69],label_info:11,label_nam:[1,2,6,11,45,46,62,69],label_process:[0,59],label_s:2,label_set:9,label_statu:11,label_typ:[0,1,2,9,10,11,17,70],labelprocess:61,labels_from_this_fil:[6,59,69],labels_test:[9,70],labels_train:[9,70],lambda:2,lambda_tol:2,languag:[23,24,59,62,68],laplacian:[52,59,62],laptop:68,larg:[2,61,66,68],larger:[40,61,62,66],largest:[10,11,56,60,62,66],lasso:[2,21,33,34,62],last:[61,66,68],lastli:[50,62,64],later:[2,9,62,66],latest:[42,51,52,60,62],latex:61,latter:64,lbfg:[21,62],lbp:[42,58,59,62],lbp_npoint:[41,42,62,66],lbp_radiu:[41,42,62,66],lda:[21,22,62],lda_shrinkag:[21,22,62],lda_solv:[21,22,62],lead:66,learn:[2,9,10,21,22,34,54,59,60,61,62,68,70],least:[2,66,68],leav:[26,61,62],led:61,leender:59,left:[2,61],length:[2,9,10,59],lengthi:69,lesion:[32,62,66],less:[61,62,66],let:69,letter:15,level:[42,51,52,59,62,70],lib:59,licens:59,lidc:59,lightweight:2,lij:9,like:[2,9,61,62,66,68,69],limit:70,line:[2,9,59,60,64,66,68,69],linear:[2,21,61,62,70],linear_model:[21,22,34,62],linearexecut:[6,17,21,62],link:[17,61,64,69,70],link_n4biasfieldcorrection_doc:60,linr:[21,62],linstretch:[0,59],linux:61,linuxdetector:4,lipoma:59,liposarcoma:59,list:[0,1,2,4,6,7,9,10,11,17,18,21,23,35,36,38,41,42,44,47,58,62,65,70],literatu:9,literatur:[9,60,66],littl:[2,68],liver:[59,70],load:[1,11,42,62,69],load_config:[1,64],load_config_xnat:11,load_data:1,load_featur:[1,61],load_iri:2,load_label:11,load_label_csv:11,load_label_txt:11,load_label_xnat:11,loc:[2,21,22,33,43,53,54,62],local:[42,59,62],locat:[6,58,61,62,66,69],location_featur:[9,57,58,62],log10:15,log:[9,15,22,41,42,51,52,58,59,61,62,64,65,68],log_featur:[9,57,58,62],log_sigma:[41,42,62,66],log_uniform:2,log_z_scor:[35,62],logarithm:[9,61],logic:61,logist:[22,62],logisticregress:[21,22,34,61,62],logit:9,logstandardscal:9,longer:[61,62],loo:[25,26,61,62],loo_cross_valid:2,look:[6,59,60,62,63,64,66,68,69,70],loop:[2,65],loss:[2,22,62,66],lot:[52,62,66,68],low:[59,66],lower:[9,11,34,50,61,62],lowerbound:11,lr_l1_ratio:[21,22,62],lr_solver:[21,22,62],lrc:[21,22,62],lrpenalti:[21,22,62],lsqr:[21,62],luckili:68,lung:59,maarten:59,machin:[2,34,59,61,62,66,68,70],macskassi:70,made:[6,59,61,62,66,68,70],maenpaa:66,magnet:66,mai:[2,62,64,66,68,69],main:[6,10,13,16,60,61,69,70],major:[53,61,62,66],majorli:[6,61],make:[2,6,10,38,40,60,61,62,64,65,68,69,70],make_scatterplot:10,make_scor:2,malign:59,manag:[0,66],mandatori:[1,2,9,10,11],manhattan:61,manhattan_import:10,mani:[0,2,9,10,28,56,60,61,62,66,68,70],manipul:70,mann:70,mannwhitneyu:[9,33,62],manual:[2,6,39,59,60,61,62,65,66,68,69],manufactur:66,map:[2,10,70],mappingproxi:[0,2,4,6,7,9,11,17,18],mark:10,marku:66,martijn:59,mask:[0,2,6,10,11,38,50,52,55,56,60,61,62,68,69],mask_contour:11,mask_file_nam:6,masked_arrai:2,masks_from_this_directori:6,masks_test:70,masks_train:70,mass:66,master:[2,60,64,70],match:[1,11,61,62,70],matlab:[9,11,23,24,59,60,62,68],matplotlib2tikz:61,matplotlib:10,matrix:[2,9,59],matter:9,matti:66,max:[1,31,32,34,41,62,64,66],max_it:[2,21,22,62],maxim:2,maximum:[2,22,42,61,62,66],maxlen:[2,39,40,61,62],mean:[1,2,6,9,24,31,32,43,61,62,65,66,70],mean_fit_tim:2,mean_score_tim:2,mean_test_scor:2,mean_train_scor:2,measur:[2,6,66,70],median:[9,43,50,62,66],medic:[59,66,68],medicin:[59,66],meet:[6,59],melanoma:59,member:2,memori:[2,39,40,61,62,70],mention:66,mesenter:59,mesh:66,messag:[2,10,61],metadata:[0,11,38,50,60,61,62,66],metadata_fil:11,metadata_test:70,metadata_train:70,metaestimatormixin:2,metastas:59,method:[0,2,6,9,10,11,15,32,34,36,44,49,50,53,54,59,61,62,65,66,68,70],metion:9,metric1:10,metric1t:10,metric2:10,metric2t:10,metric:[0,9,10,27,28,39,40,59,61,62,70],mhd:[11,70],miccai:59,michael:66,miclea:59,micro:68,microsoft:69,middl:[0,10,70],midrank:15,mimic:11,min:[9,34,41,61,62,64,66],min_object_s:[55,56,62],mine:[59,60,68],minim:[2,42,62,69,70],minimum:[22,42,50,56,61,62,66],minkov:9,minm:[49,62],minmax:[9,35,61,62],minor:[53,61,62,66],minsubjectsvalid:18,mismatch:[38,62],miss:[2,9,61],missing_valu:9,missingpi:[9,61],mixtur:11,mod:[9,23,24,61,62,64],modal:[2,9,42,52,61,62,66,70],modalityname1:[2,9],modalityname2:[2,9],mode:6,model:[1,2,6,10,15,17,34,40,58,59,61,62,68,70],model_select:[2,9],moder:[24,60,62,66],modified_hub:[21,62],modnam:1,modu:[0,2,10,17,45,46,62,69],modul:[12,21,22,34,61,62,64,70],modular:59,modulenotfounderror:59,molecular:59,momentum:66,more:[2,6,9,10,11,36,38,40,59,60,61,62,64,65,66,68,69,70],moreov:68,morpholog:[11,66],most:[2,6,9,22,62,66,68,69],most_frequ:[9,43,62],mostli:[2,9,61,62,70],mount:[2,6,61,69],move:61,mr001:0,mr002:0,mri:[52,59,62,66],mse:70,mstarmans91:[6,59,64,65,69,70],much:[40,54,61,62,66],multi:[2,59,66],multi_class_auc:2,multi_class_auc_scor:2,multi_class_relief:9,multicentr:59,multiclass:[2,6,70],multiclass_classif:6,multicor:[6,38,62],multihread:61,multilabel:[2,6,45,46,59,61,62],multilabel_typ:10,multimetric_grid_search:2,multimod:61,multipl:[0,2,9,10,32,38,60,61,62,66,68,69,70],multipli:[11,55,56,62],multiprocess:[37,62],multiresolut:66,multiscal:66,multislic:[42,58,62],multivendor:59,must:[2,59,62],mutat:59,mutlicor:2,mwu:9,mxn:2,n_1:10,n_2:10,n_blob:[55,56,62],n_classifi:15,n_compon:61,n_core:2,n_exampl:15,n_featur:[2,5,9,61],n_iter:[2,17,19,20,25,26,39,40,62],n_job:2,n_jobspercor:[2,39,40,62],n_jobsperscor:2,n_neighbor:[2,9,43,44,53,54,62],n_neighbour:9,n_neightbor:9,n_object:5,n_output:2,n_patient:9,n_sampl:[2,9,61],n_split:[2,39,40,61,62],n_splits_:2,n_test:10,n_train:10,nadeau:70,naiv:68,name:[0,2,6,9,10,11,17,22,24,36,42,48,57,58,59,61,62,66,69,70],name_of_label_predicted_for_evalu:70,nan:[2,9,32,44,61,62,66],ndarrai:2,nearest:[9,34,44,62],nearmiss:[53,62],neccesari:[61,64],neck:69,need:[2,6,9,59,61,62,64,66,68,69,70],needaccess:9,neg:[9,61,70],neg_dual_func:2,neighbor:[9,34,44,62],neighborhood:59,neighbour:[9,66],neighbourhoodcleaningrul:[2,53,62],net:9,nettyp:17,network:[0,13,17,59,61,62,64,68,69],neural:70,neurocombat:60,never:[30,60,62],new_spac:11,newest:61,newli:61,nework:0,next:[66,69,70],ngldm:[58,61,62],ngtdm:[42,52,58,59,61,62,65],nice:[61,68],niessen:59,nifti:[61,70],nii:[0,6,11,69,70],nipyp:2,nmod:0,nocrossv:2,node:[0,17,32,61,62,68,70],nofeaturesfoundexcept:7,noimagesfoundexcept:7,nois:[24,62],nomasksfoundexcept:7,nomean:9,non:[2,6,9,24,61,62,66,68,70],none:[0,1,2,4,5,6,7,9,10,11,15,17,18,21,35,51,55,56,61,62,65],nonparametr:70,nor:59,norm_tol:2,normal:[2,6,10,11,49,50,51,52,60,61,62,66,68,70],normalization_factor:10,normalize_imag:[11,60],normalize_roi:[11,49,50,62],normalize_whitespac:2,normalizescal:[51,52,62],nosegmentationsfoundexcept:7,not_label:2,notabl:61,note:[0,2,6,9,10,11,61,62,66,68,69],notic:66,notimplementederror:0,now:[61,66],npoint:66,npv:[61,70],nrrd:[11,70],nsampl:10,nsubject:[5,69],num_class:2,num_train:2,number:[2,6,9,10,11,15,20,22,26,34,38,40,42,44,54,61,62,66,68,70],numbertoextract:11,numer:[2,9,70],numf:9,numpi:[2,9,10,11,15,59,61,66],obj:59,object:[0,1,2,4,6,7,9,10,11,17,18,22,32,54,56,59,60,61,62,64,69],objectsampl:[0,59,61],observ:[2,9],obsolet:[38,62],occur:[2,9,34,59,62,63,65,70],occurr:9,odd:66,oddfeat:9,oddpati:9,odink:59,oerat:15,of_:[23,62],off:[2,66,70],offer:66,offici:59,often:[62,66,68,70],ojala:66,older:61,omit:69,onc:[2,11,60,61,66],oncolog:59,oncoradiom:[6,61],one:[0,2,6,9,10,11,26,36,48,50,61,62,64,65,66,68,69,70],onehotencod:[2,3,9,48,59,61],onehotencoderwrapp:[0,59],onevsrest:61,onevsrestclassifi:2,onli:[2,6,9,11,22,30,40,50,61,62,65,66,68,69,70],onlin:[68,69],ontolog:68,onward:2,open:[59,61,65,68,69],oper:[10,11,59,66,70],opim:2,optim:[0,2,22,40,60,61,62,63,66,70],optimiz:0,option:[0,1,2,6,9,10,11,19,21,22,23,25,27,29,31,32,33,35,37,39,41,43,45,47,49,51,53,55,57,60,61,62,64,66,69,70],order:[2,9,10,11,52,60,61,62,63,66,68],org:[2,9,21,22,34,62],organ:[66,68],orient:[11,41,42,50,58,59,60,61,62],orientation_featur:[9,57,58,62],orientationprimaryaxi:[49,50,62],origin:[2,51,52,58,60,61,62,66],original_featur:[9,57,58,62],oserror:0,other:[0,2,9,34,39,59,60,61,62,64,68,70],otherwis:[2,9,50,52,60,61,62],otsu:[11,49,50,61,62],our:[59,62,64,66,69,70],out:[2,10,11,26,61,62,68,69,70],outcom:[2,40,62,68,69],outer:[26,60,62,66],outlier:[9,61],output:[2,6,9,10,11,17,61,62,64,68,69,70],output_csv:[9,10],output_fold:7,output_hdf:2,output_itk:10,output_json:2,output_nam:10,output_name_zoom:10,output_png:[9,10],output_tex:[9,10],output_zip:10,outputfold:[2,10,69],over:[2,6,9,61,62,66,68],overal:[61,69],overfit:[30,60,61,62],overfit_scal:[2,10],overfitscal:[29,30,62],overid:61,overlai:10,overrid:[6,61],oversampl:[61,68],overview:[60,63,66,69,70],overwrit:[6,50,61,62],overwritten:0,own:[37,62,64,66,68,69],p_ngtdm:65,packag:[59,61,66,70],packagedir:61,pad:[10,17],padmo:59,page:[15,59,68,70],pairwis:11,pairwise_auc:2,panda:[2,10,69],panda_data:2,paper:[2,9,66],par:[9,23,24,62],para:2,paracheck:10,parallel:[2,6,61,62],param:[2,10],param_c:2,param_degre:2,param_distribut:2,param_gamma:2,param_grid:2,param_kernel:2,param_list:2,paramet:[0,2,6,9,10,11,22,34,40,54,59,60,61,62,63,64,68,70],parameter_optim:[0,59],parametergrid:2,parameters_al:2,parameters_est:2,parametersampl:2,parametr:[9,24,62],paramt:2,parekh:66,parent:17,pars:[1,61,62,64],part:[2,6,34,42,61,62,63,64,66,68,70],parti:9,pass:[2,61,70],path:[0,1,2,7,9,10,11,24,61,62,69],pathnotfoundexcept:7,patient001:0,patient002:0,patient1:[62,70],patient1_0:70,patient1_1:70,patient2:[62,70],patient3:[62,70],patient:[0,1,2,6,9,10,11,32,54,59,61,62,66,69,70],patient_001:69,patient_002:69,patient_featur:[9,61,70],patient_id:[2,11,17],patientclass:[61,62],patientinfo:[1,2,9,10,11],patientinfo_test:2,patientinfo_train:2,patrick:9,pattern:[59,70],pca:[2,6,34,61,62,64,70],pcatyp:[33,34,62],pce:61,pdf:9,peak:66,pearson:70,peform:69,penalti:[22,61,62],peopl:59,per:[0,1,2,9,24,56,61,62,65,66,70],per_featur:[9,23,24,62],percentag:[2,6,9,10,17,26,34,40,54,61,62,66,69,70],percentil:[9,61,66],perform:[0,2,6,9,10,17,26,30,38,40,46,59,61,62,63,68,69,70],performance_all_0:69,performance_fil:69,performance_metr:2,performance_multilabel:2,performance_singlelabel:2,person:59,peter:66,peura:66,pf_:[23,35,62],phase:[41,42,58,59,62],phase_featur:[9,57,58,62],phase_minwavelength:[41,42,62,66],phase_nscal:[41,42,62,66],phd:68,phenotyp:66,phil:59,philip:66,physic:0,pick:[62,70],pid:[10,11,61],pietikainen:66,pilot:59,pinfo:[10,17,61],pinfo_hn:69,pip:[60,61,65,69],pipelin:[0,59,61,68,70],pixel:[0,10,42,52,62,66],place:64,placehold:9,platform:[59,68,69],pleas:[2,6,9,59,60,62,63,64,65,66,69,70],plot:[0,9,16,59,61],plot_bar:10,plot_barchart:[0,59],plot_boxplot_featur:[0,59],plot_boxplot_perform:[0,59],plot_error:[0,59],plot_estimator_perform:[0,59],plot_hyperparamet:[0,59],plot_im_and_overlai:10,plot_imag:[0,59,61],plot_prc_cic:10,plot_pvalues_featur:[0,59],plot_ranked_imag:10,plot_ranked_percentag:10,plot_ranked_posterior:[10,61],plot_ranked_scor:[0,59],plot_roc:[0,59],plot_roc_c:10,plot_single_prc:10,plot_single_roc:10,plot_svm:61,plot_svr:61,plot_test:9,plotminmaxrespons:[0,59],plotrankedscor:61,plu:[2,24,62,70],pluge:0,plugin:[0,2,21,22,40,61,62,65,68],png:[0,10,61],point:[2,10,42,62,69],pointint:10,pointsar:10,poli:[2,21,62],polynomi:[22,62,70],port:61,posit:[2,9,10,34,62,66,70],possibl:[2,9,59,61,66,68,70],post:69,posterior:[6,10,70],posteriors_csv:10,potenti:64,ppv:70,practic:68,prax:66,prc_csv:10,prc_png:10,prc_tex:10,pre:61,pre_dispatch:2,precis:[10,61,66,70],precomput:69,precrop:[51,52,62],predict:[2,5,6,9,10,15,37,57,59,60,61,62,65,66,68,69,70],predict_label:[6,61,69],predict_log_proba:2,predict_proba:[2,61],predictions_on:15,predictions_sorted_transpos:15,predictions_two:15,predictproba:61,predit:61,preflighcheck:61,preflightcheck:[0,59,61],prepar:[11,59],preprint:59,preprocess:[0,2,3,9,37,38,50,59,61,68,70],preprocess_nod:0,preprocessor:[0,32,59,61,62,64],preprocss:2,present:[2,59,61,66],preserverd:[24,62],prevent:61,previou:[68,70],previous:[61,68],primari:[50,62],primary_axi:11,princip:66,principl:[34,59,62,68,70],print:[2,7,9,10,61,69,70],probabl:[2,15,69],probe:59,problem:[2,59,61,68],procedur:[9,62,70],proceed:[59,70],process:[0,2,6,15,38,59,60,61,62,68,70],process_fit:2,processpoolexecut:17,produc:[2,66],program:[23,62,68],progress:[2,61],project:[5,11,61],project_nam:5,projectid:[45,46,62],proof:59,proper:[0,61],properli:61,properti:[2,66],prostat:59,proven:68,provid:[0,2,6,10,11,17,24,28,38,49,50,60,62,63,66,69,70],provost:70,pseudo:2,psycholog:9,publish:15,purpos:[0,30,62],push:59,put:[10,61,62,70],pvalu:15,pxcastconvert:61,pyradiom:[1,3,9,37,51,52,57,59,61,64,65,66],python3:61,python:[5,9,23,59,60,61,62,64,68,69],python_intro:60,pywavelet:65,qda:[21,22,62],qda_reg_param:[21,22,62],qualiti:2,quantifi:66,quantit:[59,66,68],question:68,quick:[59,62],quickli:66,quit:[62,68],qxm:2,radial:[66,70],radian:[42,62,66],radii:[42,62],radiograph:66,radiolog:[59,66],radiom:[0,9,60,62,63,70],radiomix:[6,7,61],radiu:[10,11,42,50,56,62,66],rais:[2,61],rajic:59,ran:[2,61,69],random:[2,5,24,26,34,61,62,70],random_se:2,random_search:2,random_search_paramet:2,random_split:[25,62],random_split_cross_valid:2,random_st:[2,9],randomizedsearchcv:2,randomizedsearchcvfastr:2,randomizedsearchcvjoblib:2,randomli:[2,34,62],randomoversampl:[53,62],randomsearch:2,randomst:2,randomundersampl:[53,62],rang:[10,11,22,34,54,62,66],rank:[6,9,10,28,34,40,61,62,68,70],rank_:2,rank_test_scor:2,ranked_pid:10,ranked_scor:10,ranked_truth:10,rankedposterior:61,rankedsvm:[0,59,61],ranking_scor:[2,39,40,62],ranksvm:2,ranksvm_test:2,ranksvm_test_origin:2,ranksvm_train:2,ranksvm_train_old:2,rate:[10,22,62,70],rater:9,rather:2,ratio:[10,22,62,66],rational:63,raw:[11,66],rbf:[2,21,62],read:[1,2,11,68,69,70],read_hdf:69,reader:61,readthedoc:[0,42,51,52,54,59,60,61,62],reason:[2,66],recal:[10,61,70],receiv:[10,15,70],recommend:[2,22,24,59,60,62,64,66,68,69],recommmend:69,recreat:2,reduc:[2,59,61],reduct:[61,68],redund:[61,66],ref:2,refactor:61,refer:[0,1,2,3,4,6,7,9,10,11,15,17,18,37,61,62,64,66,68],refit:[2,40,61,62],refit_and_scor:2,refit_ensembl:10,refit_workflow:[2,39,40,62],reflect:66,regard:59,regardless:69,region:[6,66],registr:[0,38,59,61,62,68,70],registrationnod:[37,38,62],regress:[2,6,10,17,22,46,59,61,62,69,70],regressor:[0,59,60,61],regular:[22,62,70],rel:2,relat:[0,66],releas:[61,68],relev:[60,64,66,68,70],reli:66,reliabl:9,relief:[0,2,34,59,61,62],reliefdistancep:[33,34,62],reliefnn:[33,34,62],reliefnumfeatur:[33,34,62],reliefsamples:[33,34,61,62],reliefsel:2,reliefus:[33,34,62],remov:[9,10,38,56,60,61,62],remove_small_object:[55,56,62],removeconst:10,renam:61,rencken:59,repeat:[2,62],repetit:66,replac:[2,9,44,61,62,64,65],replacenan:[2,61],report:70,repositori:[59,69],repres:[2,66],reproduc:[61,68],requir:[0,2,6,22,59,61,62,65,68,69,70],resampl:[2,3,11,49,50,54,59,60,61,70],resample_imag:11,resampled_imag:11,resampledpixelspac:[51,52,62],resampling_spac:[49,50,62],research:[59,66,68],resourc:[0,11,13,59,65,68],respect:[2,9,56,60,62,69,70],result:[2,9,10,38,50,59,61,62,66,68],ret:2,retreiv:11,retriev:66,return_al:2,return_estim:2,return_n_test_sampl:2,return_paramet:2,return_tim:2,return_train_scor:2,returnplot:10,revert:61,review:66,rfmax_depth:[21,22,62],rfmin_samples_split:[21,22,62],rfn_estim:[21,22,62],rfr:[21,62],rgrd:[58,61,62],rgrd_featur:[9,57,58,62],ridg:[21,61,62],right:70,ring:[11,55,56,60,61,62],risk:[59,70],rms_score:2,rng:2,robust:[9,35,59,61,62,66],robust_z_scor:[9,35,62],robustscal:[9,61],robuststandardscal:[9,61],roc:[6,10,15,61,70],roc_comparison:15,roc_csv:10,roc_png:10,roc_tex:10,roi:[11,50,52,59,61,62,70],roi_dilate_radiu:11,roidetermin:[11,49,50,62],roidil:[49,50,62],roidilateradiu:[49,50,62],rokwa:9,root:[2,6],rosset:70,rotat:[50,62,66],rough:66,round:[2,22,61,62],rounded_list:2,routin:[66,68],row:[2,9,66],rtstructread:61,run:[2,6,9,59,61,62,65,68,70],runtim:[2,61],rvs:2,safe:64,saga:[21,62],sagit:[51,61,62],sai:60,same:[1,2,9,10,22,32,38,60,61,62,66,68,69,70],samefeat:9,sampl:[0,1,2,9,10,22,34,40,54,61,62,70],sample_s:9,sample_weight:15,sampler:2,sampleswarn:18,sampling_strategi:[2,53,54,62],sar:2,sar_scor:2,sarcoma:59,satur:66,save:[0,2,5,9,10,38,40,61,62,66,69,70],save_config:[0,64],save_data:2,save_memori:10,scale:[2,9,21,22,33,36,42,43,52,53,54,61,62,66,68],scaler:[0,2,30,59,61,62,64],scaling_method:[35,36,62],scan:[62,66,69],scanner:66,scatterplot:[0,59],schoot:59,scienc:70,scikit:[2,9,21,22,34,60,62],scipi:2,score:[2,6,9,10,17,40,50,61,62,63,70],score_tim:2,scorer:2,scorer_:2,scorers_dict:2,scoring_method:[2,6,7,39,40,62],scoring_paramet:2,script:[9,60,61,64,65,68,69,70],script_path:69,scroll:70,search:[2,6,9,34,40,59,61,62,64,65],searchcv:[0,10,59,61,64],sebastian:59,second:[2,9,15,24,62,66],section:[62,69,70],see:[0,1,2,4,6,7,9,10,11,17,21,22,34,38,42,51,52,54,59,60,61,62,64,65,66,69,70],seed:[2,26,61,62],seem:[61,68],seen:[2,70],seg:[17,61],seg_liver_mr:70,seg_tumor1_mr:70,seg_tumor2_mr:70,seg_tumor_mr:70,segment:[0,6,10,11,17,38,56,60,61,62,66,68,69],segmentation_file_nam:[6,69],segmentations1:70,segmentations2:70,segmentations_from_this_directori:[6,69],segmentations_test:70,segmentations_train:[6,70],segmentix:[0,1,3,37,38,52,59,60,61,70],segmentix_test:[0,12],segradiu:[55,56,62],segtyp:[55,56,62],sel:9,select:[2,6,9,11,22,34,52,59,61,62,68,70],selected_label:6,selectfeatgroup:[3,34,59],selectfrommodel:[33,34,61,62],selectfrommodel_estim:[33,34,62],selectfrommodel_lasso_alpha:[33,34,62],selectfrommodel_n_tre:[33,34,62],selectgroup:[0,59],selectindividu:[0,59],selectmodel:2,selectmulticlassrelief:9,selectormixin:9,self:[2,4,7,9,11,17,22,62,65],selfeat_vari:9,semant:[0,6,58,59,61,62],semantic_featur:[9,57,58,62],semantics_from_this_fil:6,semantics_test:70,semantics_train:70,semf_:[23,35,62],semicolon:61,sensibl:66,sensit:70,separ:[2,6,21,23,30,35,36,41,61,62,70],sequenc:[0,2,70],seri:6,seriou:60,serpar:61,serv:[0,66,68,70],session:5,set:[0,1,2,5,6,9,10,15,17,22,30,38,40,44,50,60,61,62,64,65,66,68,69,70],set_fixed_split:6,set_multicore_execut:[6,69],set_tmpdir:[6,69],settin:2,settings_dict:1,setup:[6,61],sever:[0,6,9,11,60,61,62,65,66,68,70],sex:[9,41,62,66,70],sf_:[23,62],sf_compact:9,sgd:[21,22,62],sgd_alpha:[21,22,62],sgd_l1_ratio:[21,22,62],sgd_loss:[21,22,62],sgd_penalti:[21,22,62],sgdr:[21,62],shape:[2,9,41,42,52,58,59,62],shape_featur:[9,57,58,62],shear:68,sheet:70,shift:[24,62],should:[0,1,2,6,9,10,11,24,36,38,40,42,54,56,60,61,62,70],show:[2,10,61,69,70],shown:68,shrink:2,shrinkag:[22,62],shrout:9,shuffle_estim:10,shutil:61,siemen:66,sigma:[9,15,66],sign:[2,9],signal:15,signatur:[2,4,7,9,11,17,59],signific:[10,70],significantli:62,similar:[2,9,60,61,64,65,66,68,69,70],similarli:64,simpl:[6,60,66,68,69],simpleelastix:70,simpleitk:[50,60,62,70],simpler:68,simplest:70,simplevalid:18,simpleworc:[0,59,60,61,69,70],simpli:[24,59,61,62,65,69,70],simplifi:69,simultan:[2,68],singel:6,singl:[2,6,10,11,15,24,40,42,44,59,60,61,62,63,70],single_class_relief:9,singleclass:2,singlelabel:[2,17,45,46,62],singleton:2,sink:[0,17,61,64,68,70],sink_data:[0,13,17,70],site:[2,59],sitkbsplin:[51,52,62],six:66,size:[2,10,17,34,40,42,59,61,62,70],size_alpha:2,skew:66,skip:[36,61,62,69,70],skip_featur:[9,35,36,62],sklearn:[2,9,10,21,22,34,39,61,62,64],slack:[22,62],sleijfer:59,slice:[0,2,10,56,61,62,66,70],slicer:[0,10,59,61],slight:2,slightli:69,slow:61,small:[9,56,60,61,62,66],smaller:[54,62,66],smallest:2,smart:[10,62],smit:59,smote:[2,53,61,62],smoteen:2,smoteenn:[53,62],smotetomek:[53,62],snapshot:70,sne:[6,70],societi:59,soft:59,softwar:[24,59,62,68],sole:66,solid:66,solut:[2,65],solv:[65,68],solver:[22,61,62],some:[0,2,6,61,62,64,68,69,70],somenam:[62,70],someon:68,sometim:61,sort:[2,15,61,69],sourc:[0,1,2,4,5,6,7,9,10,11,13,15,16,17,18,59,61,62,64,66,68,69],source_data:[0,13,70],space:[2,9,10,11,34,50,60,61,62,64,66,70],span:2,spars:[9,70],spawn:[0,2],spawner:0,spearman:70,specif:[2,9,22,48,62,64,65,66,68,69,70],specifi:[0,2,6,11,22,34,38,40,48,54,62],speed:[6,69],spend:2,spheric:66,split0_test_scor:2,split0_train_scor:2,split1_test_scor:2,split1_train_scor:2,split2_test_scor:2,split2_train_scor:2,split:[2,9,17,22,26,61,62,66,68,70],springer:66,squar:[2,10,70],squared_epsilon_insensit:[21,62],squared_hing:[21,62],squared_loss:[21,62],src:2,ssh:69,stabl:[0,9,21,22,34,54,61,62],stack:1,standalon:[17,61],standard:[6,9,42,59,61,62,66,69,70],standardis:59,standardscal:9,starman:59,start:[2,59,61,62,65,68],stat:[2,10,69],state:[0,2,28,61,62,64,69],statement:[11,64],staticmethod:18,statist:[0,2,9,10,16,34,59,61,62,66,69,70],statisticalsel:2,statisticaltest:61,statisticaltestfeatur:[0,59,61],statisticaltestmetr:[33,34,62],statisticaltestthreshold:[0,33,34,59,62],statisticaltestus:[33,34,62],statsticaltestthreshold:61,statu:[2,11,59],std:9,std_fit_tim:2,std_score_tim:2,std_test_scor:2,std_train_scor:2,stefan:59,step:[2,42,60,61,62,63,66,68,70],still:[61,69,70],stimul:59,stop:[11,61],store:[2,6,7,69,70],str:[2,61],straight:[60,68],strategi:[2,9,10,43,44,54,59,61,62],stratif:59,stratifi:[2,17],stratifiedkfold:2,strenght:[22,62],strength:[22,62,66],stretch:10,string:[0,1,2,6,9,10,11,21,23,35,39,40,41,45,47,61,62,70],stromal:59,strongli:69,struct:61,structer:66,structur:[66,69,70],stuck:69,student:[9,68,70],studi:[0,59,68],studio:69,stwstrategyhn1:69,sub:[0,66],subfold:[6,61,69],subgroup:66,subject:[2,5,6],subkei:[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,62],subpackag:59,subset:69,substr:[9,24,36,48,62],subtract:[11,55,56,61,62],succeed:61,success:2,suffici:70,suggest:[2,64],suit:[0,2,11],suitabl:[59,66],sun2014fast:15,sun:15,suppli:[1,2,10,42,50,54,56,61,62,70],support:[2,9,26,50,59,61,62,65,66,68,70],suppos:62,sure:[6,64,65,70],surfac:66,surfsara:69,surgeri:59,surgic:59,surrog:2,surround:66,surveil:59,surviv:[6,10,59,70],svc:2,svd:[21,62],svm:[2,6,10,21,22,61,62],svmc:[21,22,62],svmcoef0:[21,22,62],svmdegre:[21,22,62],svmgamma:[21,22,62],svmkernel:[21,22,62],svr:[2,6,21,62],symlink:61,symmetri:66,symposium:59,synthet:[9,10],synthetictest:9,system:[0,2,62,66,70],tabl:[2,70],tadpol:[2,70],tag:[41,42,61,62,66,70],take:[2,9,40,61,62,64,70],taken:10,tandfonlin:9,target:2,task:68,techniqu:[62,66],tedious:68,tell:[6,64,70],tempdir:[61,69],tempfold:2,temporari:[0,6,61,69],tempsav:[2,37,38,62],term:[22,34,61,62,68],terminolog:59,test:[0,2,6,9,10,15,26,30,34,38,40,59,61,62,69,70],test_combat:[0,59],test_combat_fastr:16,test_data:2,test_help:[0,59],test_iccthreshold:[0,59],test_invalidlabelsvalidator_columnsubstr:16,test_invalidlabelsvalidator_patientcolumn:16,test_invalidlabelsvalidator_patientsubstr:16,test_invalidlabelsvalidator_validconfig:16,test_metr:10,test_plot_error:[0,59],test_rs_ensembl:2,test_sampl:10,test_sample_count:2,test_scor:[2,39,62],test_score_dict:2,test_siz:[2,17,25,26,39,40,62],test_target:2,test_valid:[0,59],tex:[10,61],text:2,textur:[42,58,59,62],texture_featur:9,texture_gabor:[41,42,62],texture_gabor_featur:[9,57,58,62],texture_glcm:[41,42,51,52,62],texture_glcm_featur:[9,57,58,62],texture_glcmm:[41,42,62],texture_glcmms_featur:[9,57,58,62],texture_gldm:[51,52,62],texture_gldm_featur:[57,58,62],texture_gldzm_featur:[9,57,58,62],texture_glrlm:[41,42,51,52,62],texture_glrlm_featur:[9,57,58,62],texture_glszm:[41,42,51,52,62],texture_glszm_featur:[9,57,58,62],texture_lbp:[41,42,62],texture_lbp_featur:[9,57,58,62],texture_ngldm_featur:[9,57,58,62],texture_ngtdm:[41,42,51,52,62],texture_ngtdm_featur:[9,57,58,62],tf_glcm_contrastd1:66,than:[2,54,61,62],thei:[2,61,62,63,66,69,70],them:[2,61,62,68,70],themselv:66,therebi:[59,61,68,70],therefor:[0,6,9,60,61,64,66,68,69,70],thi:[0,2,6,9,10,32,36,40,48,50,54,59,60,61,62,63,64,65,66,67,68,69,70],thick:66,thing:[61,62,69],third:9,thoma:59,thomeer:59,those:[2,6,9,64,66,70],thread:[37,61,62],three:[2,66],thresh:[9,10],threshold:[2,9,10,16,34,50,54,61,62,66],threshold_annot:10,threshold_clean:[2,53,54,62],through:[0,2,11,17,50,59,61,62,66,68,69,70],throughput:66,thu:[2,9,59,60,61,62,66,68,70],tibshirani:70,tiff:[11,70],tikzplotlib:61,timbergen:59,time:[2,10,26,34,40,54,61,62,66,68,69,70],timer:61,timo:66,tip:59,tissu:59,titl:15,tmp:6,tmpdir:[6,69],todo:[2,9],togeth:[61,64],tol:2,toler:2,tomek:2,tomographi:59,tone:59,too:66,tool:[0,6,37,38,59,60,61,62,64,67,68,69,70],toolbox:[9,57,58,59,61,62,65,66,70],top50:2,top:[10,61],topi:66,toshiba:66,total:[2,66],towardsdatasci:62,tpr:10,trace:[65,69],track:2,trade:2,train:[0,2,6,10,22,26,30,34,38,40,61,62,70],train_data:2,train_scor:2,train_score_dict:2,train_target:2,train_test_split:2,trainclassifi:[0,10,59,61,64],transact:[2,66],transform:[2,9,38,61,62,64,66,70],transformationnod:[37,38,62],transformermixin:9,transformix:[0,37,59,61,62],transpos:[11,60,61],transpose_imag:11,travi:61,treat:62,tree:[22,34,62,70],tri:[2,68],trick:59,trigger:66,truth:[2,10,61,70],tsampl:10,ttest:[9,33,61,62],tube:66,tubular:66,tumor:[59,69,70],tumour:59,tune:[2,62,68],tupl:2,turn:61,tutori:[16,59,62,65],two:[0,2,9,10,15,21,33,41,43,53,61,62,66,69,70],txt:[0,1,2,6,9,10,61,62,70],type:[0,2,4,7,9,10,11,17,22,25,26,34,38,59,61,62,64,66,68,70],typeerror:[0,2],typegroup:61,typic:70,typo:61,udr:2,unadjust:15,unaffect:[24,62],unag:11,uncorrect:70,under:[2,15,59,61,62,66,70],underli:2,underscor:70,understand:68,unfit:2,unfortun:65,uniform:[2,22,54,61,62,64,66],uniformli:2,uniqu:[2,66],unit:[61,62],univari:[2,6,70],univers:[2,59],unless:2,unreleas:[],unround:61,unsuccesful:61,unsuit:61,unsupervis:2,until:2,updat:61,upgrad:61,upon:[6,62],upper:[34,62],upperbound:[11,50,62],uri:61,url:[11,45,46,61,62],urltyp:61,usabl:2,usag:[2,40,61,62,66,70],usd:9,use:[0,2,6,9,10,11,17,20,22,24,26,28,30,32,34,38,43,44,48,50,52,58,60,61,62,64,66,68,69,70],use_fastr:2,useag:9,used:[0,1,2,6,9,10,11,22,26,28,30,34,38,40,42,44,46,50,52,54,56,58,59,61,62,64,66,68,69,70],useful:[2,9,38,62,70],usemask:11,usepca:[33,34,62],user:[2,6,60,66,67,69],usersmynamefeaturefold:6,usersmynameimagefold:6,usersmynamemaskfold:6,usersmynamesegmentationfold:6,uses:[2,6,9,61,64,65,66,67],using:[0,2,6,9,17,22,24,26,28,34,40,44,50,52,59,60,61,62,64,65,66,68,69,70],usual:66,util:2,v600e:59,val:0,valid:[0,2,6,9,10,17,26,38,40,59,61,62,70],validationm:[26,62],validatorsfactori:18,valu:[0,2,6,9,10,11,15,34,39,42,44,48,52,60,61,62,64,66,69,70],value1:62,value2:62,valueerror:0,van:[59,66],vari:[2,52,61,62,66,68],variabl:[0,10,24,60,61,62,69],varianc:[2,9,15,33,34,61,62,66],variancethreshold:[0,34,59,61,62],variancethresholdmean:9,variant:68,variat:[24,62],varieti:[6,59,66],variou:[2,10,59,61,62,64,67,68,70],varsel:2,vector:[2,9],veenland:59,veldt:59,vendor:59,verbos:[2,5,9,10,61],verhoef:59,veri:[2,68],vermeulen:59,version:[15,24,61,62,65,66],verson:61,versu:59,vessel:[41,42,58,59,62],vessel_featur:[9,57,58,62],vessel_radiu:[41,42,62,66],vessel_scale_rang:[41,42,62,66],vessel_scale_step:[41,42,62,66],vfs:[0,61],via:69,vincent:59,virtual:65,virtualenv:69,vishwa:66,visit:64,visser:59,visual:[66,69],vizual:61,vol:70,volum:[15,59,66],voort:59,voxel:[56,62,66],voxelarrayshift:[51,52,62],wai:[62,66,70],want:[0,6,11,59,60,62,66,69,70],warn:[2,61],warp:70,wavelength:[42,62],wavelet:[51,52,58,59,61,62],wavelet_featur:[9,57,58,62],weak:[0,2,4,6,7,9,11,17,18],week:65,weichao:15,weight:[2,22,61,62],weigth:[34,62],welch:[9,33,62,70],well:[11,59,61,62,64,66,68,69,70],were:[61,64,66,68,70],weus:70,what:[64,66],when:[0,2,6,9,10,17,22,26,28,34,36,40,44,60,61,62,64,65,66,68,69,70],whenev:2,where:[2,10,59,61,68,69],wheter:[30,62],whether:[1,2,6,9,10,11,20,28,38,42,46,48,50,52,56,61,62,63,66,69],which:[0,2,6,7,9,10,11,24,34,36,38,40,48,52,60,61,62,63,64,65,66,68,69,70],whitnei:70,whole:[40,62,68],why:62,wich:2,wide:[59,66],width:[52,59,62,70],wijnenga:59,wiki:[1,2,9,10,11],wilcoxon:[2,9,33,62,70],wildcard:6,willemssen:59,window:[22,61,62,69],wip:[9,10,45,46,59,60,62,63,64],with_mean:9,with_std:9,within:[61,63,65,66,68,70],withing:[50,62],without:[2,61],wonder:68,worc:[1,2,4,5,6,7,9,10,11,13,15,16,17,18,22,37,39,42,48,60,61,62,63,64,66,67,68,69],worc_:69,worc_config:[0,59,61,62],worcassertionerror:0,worccastconvert:61,worccastcovert:61,worcdirectorydetector:4,worcerror:0,worcflow:59,worcindexerror:0,worcioerror:0,worckeyerror:[0,59],worcnotimplementederror:0,worcscal:9,worctutori:[6,59,69,70],worctutorialsimple_travis_multiclass:[0,59],worctutorialsimple_travis_regress:[0,59],worctypeerror:0,worcvalueerror:[0,59],worcworc:64,work:[11,61,66,68],workaround:2,workflow:[0,2,6,10,40,61,62,63,64,66,68,69,70],would:[62,66,68,69,70],wrap:[2,60,61,64,68],wrapper:[2,60,64,70],write:10,written:[2,9,10],wtype:0,www:[9,62],x_test:[2,9],x_train:[2,9,10],xgb:[22,62],xgb_boosting_round:[21,22,62],xgb_colsample_bytre:[21,22,62],xgb_gamma:[21,22,62],xgb_learning_r:[21,22,62],xgb_max_depth:[21,22,62],xgb_min_child_weight:[21,22,62],xgbclassifi:[21,62],xgboost:[60,61,62],xgbregressor:[21,62],xgdboost:[60,61],xlsx:[2,7],xml:64,xnat:[11,61,69],xnat_url:5,y_predict:[2,10],y_score:[2,10],y_test:2,y_train:[2,9,10],y_truth:[2,10],yandexdataschool:15,year:15,yet:[6,11,61],yield:2,yml:61,you:[0,2,6,11,17,48,54,59,60,61,62,64,65,66,68,69,70],your:[0,2,6,30,37,38,40,46,52,59,61,62,64,65,69],yourself:[59,68],yspace:9,z_score:[9,11,35,49,62],zero:[9,44,61,62],zij:9,zip:[10,61,69],zone:59,zoomfactor:10,zwanenburg:66},titles:["WORC Package","IOparser Package","classification Package","<no title>","detectors Package","exampledata Package","facade Package","helpers Package","fastrconfig Package","featureprocessing Package","plotting Package","processing Package","resources Package","fastr_tests Package","fastr_tools Package","statistics Package","tests Package","tools Package","validators Package","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","<no title>","WORC: Workflow for Optimal Radiomics Classification","Additional functionality","Changelog","Configuration","Data Mining Methods","Developer documentation","FAQ","Radiomics Features","Resource File Formats","Introduction","Quick start guide","User Manual"],titleterms:{"0rc1":61,"boolean":65,"class":11,"function":60,"import":69,Added:61,Adding:64,The:[69,70],actual:69,addexcept:[0,65],addit:60,advancedsampl:2,analysi:[63,69],arrai:65,attribut:70,basicworc:6,begin:65,bigr:65,bin:66,binari:66,bootstrap:62,calcfeatures_test:13,chang:61,changelog:61,choic:66,classif:[2,59,62,63],classifi:60,cluster:65,column:65,combat:[9,60,62],command:70,compon:63,compute_ci:10,config_io_classifi:1,config_io_combat:1,config_io_pyradiom:1,config_preprocess:1,config_segmentix:1,config_worc:1,configbuild:7,configur:62,construct:70,construct_classifi:2,content:62,crash:65,create_example_data:5,createfixedsplit:[2,17],creation:62,crossval:2,crossvalid:62,data:[63,64,70],datadownload:5,debug:70,decomposit:9,definit:70,delet:65,delong:15,depend:66,detector:4,develop:[59,64],dicom:66,differ:[65,66],dimension:63,document:[59,64],elastix:17,elastix_para:70,elastix_test:13,ensembl:62,entri:65,error:65,estim:2,evalu:[17,62,70],exampl:[64,70],exampledata:5,except:7,execut:[65,70],experi:[65,69],extract:66,extractnlargestblobsn:11,facad:6,fals:65,faq:65,fastr:68,fastr_test:13,fastr_tool:14,fastrconfig:8,feat_out_0:65,featpreprocess:62,featsel:62,featur:[63,64,65,66,70],featureconvert:9,featureprocess:9,featuresc:62,file:[65,67,70],file_io:1,filter:66,first:65,fitandscor:2,fix:[61,66],format:67,found:65,from:63,full:66,function_bas:65,gabor:66,gaussian:66,gener:62,given:65,glcm:66,gldm:66,glrlm:66,glszm:66,grai:66,groupwis:63,guid:69,hdf5:65,helper:[7,11],histogram:66,hyperoptim:[62,64],icc:60,iccthreshold:9,imag:[60,66,70],imagefeatur:62,imput:[9,62,63],indexerror:65,indic:[59,65],infer:17,input:[69,70],instal:[65,69],integ:65,interact:[62,70],introduct:[62,68],iopars:1,job:65,keep:65,label:[62,65,70],label_process:11,labels_from_this_fil:65,laplacian:66,lbp:66,learn:63,length:66,level:66,lib:65,like:65,line:65,linstretch:10,local:66,log:66,look:65,machin:63,manual:70,mask:70,matrix:66,metadata:70,method:[63,64],metric:2,mine:63,model:63,modul:[0,1,2,4,5,6,7,8,9,10,11,13,15,16,17,18,59,65],modular:68,modulenotfounderror:65,must:65,name:65,need:65,neighborhood:66,network:70,ngtdm:66,numpi:65,obj:65,object:70,objectsampl:2,occur:66,onehotencod:[62,63],onehotencoderwrapp:9,optim:[59,68],orient:66,other:66,packag:[0,1,2,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,65,69],paramet:66,parameter_optim:2,patient:65,pattern:66,pca:63,phase:66,plot:10,plot_barchart:10,plot_boxplot_featur:10,plot_boxplot_perform:10,plot_error:10,plot_estimator_perform:10,plot_hyperparamet:10,plot_imag:10,plot_pvalues_featur:10,plot_ranked_scor:10,plot_roc:10,plotminmaxrespons:10,preflightcheck:18,preprocess:[11,60,62],preprocessor:9,princip:63,process:[7,11,64],pyradiom:62,queue:65,quick:69,radiom:[59,66,68],rankedsvm:2,reduct:63,refer:59,registr:60,regress:63,regressor:2,relief:[9,63],resampl:[62,63],resourc:[12,67],result:69,roi:66,run:[66,69],scale:63,scaler:9,scatterplot:10,searchcv:2,segment:70,segmentix:[11,62],segmentix_test:13,select:[63,66],selectfeatgroup:62,selectgroup:9,selectindividu:9,semant:[66,70],shape:66,simpleworc:[6,65],site:65,size:66,slicer:17,some:65,sourc:70,standard:68,start:69,statist:[15,63],statisticaltestfeatur:9,statisticaltestthreshold:9,submit:65,subpackag:[0,6,12],surviv:63,tabl:59,terminolog:68,test:[16,63,64],test_combat:16,test_help:16,test_iccthreshold:16,test_plot_error:16,test_valid:16,textur:66,tip:69,tone:66,tool:17,toolbox:64,trainclassifi:2,transformix:17,trick:69,tutori:69,type:65,univari:63,unreleas:[],used:65,user:[59,70],valid:18,varianc:63,variancethreshold:9,vessel:66,wavelet:66,welcom:59,where:65,width:66,worc:[0,59,65,70],worc_config:8,worckeyerror:65,worctutorialsimple_travis_multiclass:16,worctutorialsimple_travis_regress:16,worcvalueerror:65,work:65,workflow:59,would:65,your:70,zone:66}})
\ No newline at end of file
diff --git a/WORC/doc/_build/html/static/changelog.html b/WORC/doc/_build/html/static/changelog.html
index 56e4d2aa..19f60235 100644
--- a/WORC/doc/_build/html/static/changelog.html
+++ b/WORC/doc/_build/html/static/changelog.html
@@ -8,7 +8,7 @@
- Changelog — WORC 3.4.2 documentation
+ Changelog — WORC 3.4.3 documentation
@@ -64,7 +64,7 @@
- 3.4.2
+ 3.4.3
@@ -99,140 +99,145 @@
- Developer documentation
- Resource File Formats
- Changelog
-- 3.4.2 - Unreleased
+- 3.4.3 - 2021-06-02
-- 3.4.1 - 2021-05-18
-- Fixed
-- Changed
-- Added
+- 3.4.2 - 2021-05-27
-- 3.4.0 - 2021-02-02
-- Fixed
-- Changed
+- 3.4.1 - 2021-05-18
-- 3.3.5 - 2020-10-21
+- 3.4.0 - 2021-02-02
-- 3.3.4 - 2020-10-06
+- 3.3.5 - 2020-10-21
-- 3.3.3 - 2020-09-11
+- 3.3.4 - 2020-10-06
-- 3.3.2 - 2020-08-19
-- Fixed
-- Added
-- Changed
+- 3.3.3 - 2020-09-11
-- 3.3.1 - 2020-07-31
-- Changed
-- Fixed
+- 3.3.2 - 2020-08-19
-- 3.3.0 - 2020-07-28
-- Added
+- 3.3.1 - 2020-07-31
-- 3.2.2 - 2020-07-14
+- 3.3.0 - 2020-07-28
-- 3.2.1 - 2020-07-02
+- 3.2.2 - 2020-07-14
-- 3.2.0 - 2020-06-26
+- 3.2.1 - 2020-07-02
-- 3.1.4 - 2020-05-26
+- 3.2.0 - 2020-06-26
-- 3.1.3 - 2020-01-24
+- 3.1.4 - 2020-05-26
-- 3.1.2 - 2019-12-09
+- 3.1.3 - 2020-01-24
-- 3.1.1 - 2019-11-28
+- 3.1.2 - 2019-12-09
-- 3.1.0 - 2019-10-16
+- 3.1.1 - 2019-11-28
-- 3.0.0 - 2019-05-08
+- 3.1.0 - 2019-10-16
-- 2.1.3 - 2019-04-08
-- Changed
+- 3.0.0 - 2019-05-08
-- 2.1.2 - 2019-04-02
-- Added
-- Changed
-- Fixed
+- 2.1.3 - 2019-04-08
-- 2.1.1 - 2019-02-15
+- 2.1.2 - 2019-04-02
-- 2.1.0 - 2018-08-09
+- 2.1.1 - 2019-02-15
-- 2.0.0 - 2018-02-13
@@ -308,11 +313,27 @@ ChangelogKeep a Changelog
and this project adheres to Semantic Versioning
-
-3.4.2 - Unreleased¶
+
+3.4.3 - 2021-06-02¶
Fixed¶
+SimpleWORC and BasicWORC now support multilabel workflows.
SimpleWORC and BasicWORC now support use of masks.
+
+
+Added¶
+
+Unit testing for multilabel workflows.
+
+
+
+3.4.2 - 2021-05-27¶
+
+Fixed¶
+
Bug in flattening of plot_ranked_posteriors function.
Bug in plot_images: could not handle 2D images when applying slicing.
Bug in precision-recall curve.
Fixed
Preflighcheck now also accepts labels from txt or XNAT.
-
-
-3.4.1 - 2021-05-18¶
-
-Fixed¶
+
+3.4.1 - 2021-05-18¶
+
+Fixed¶
-
-3.4.0 - 2021-02-02¶
-
-Fixed¶
+
+3.4.0 - 2021-02-02¶
+
+Fixed¶
MAJOR: Bug in SearchCV sorting of output files.
Bug in StatisticalTest for Manhattan plot.
Fixed¶
Fix random states in boosting estimators.
-
-Changed¶
+
+Changed¶
IMPORTANT: previously, used f1_score based on estimator.predict function.
Now, use predict_proba.
New defaults for random-search and ensemble.
-
-Added¶
+
-
-3.3.5 - 2020-10-21¶
-
-Fixed¶
+
+3.3.5 - 2020-10-21¶
+
+Fixed¶
Some function cleaning: removing redundant parts / variables.
-
-Changed¶
+
+Changed¶
Part of developper documentation for addinf methods to hyperoptimization.
Default config: SelectFromModel incorporated, so now also use
that in feature selection step.
-
-
-3.3.4 - 2020-10-06¶
-
-Fixed¶
+
+3.3.4 - 2020-10-06¶
+
+Fixed¶
Bugfixes in some error messages.
If a classifier cannot give a score, use the prediction instead.
Fixed
Bugfix: use f1-weighted score in SimpleWORC binary classification.
-
-Changed¶
+
+Changed¶
There are no longer ‘’patient_features’’ in PREDICT: these are extracted
from the DICOM tags and are thus now called ‘’dicom_features.
As bootstrapping is now more efficient, increase default to 1000 iterations.
-
-
-3.3.3 - 2020-09-11¶
-
-Fixed¶
+
+3.3.3 - 2020-09-11¶
+
+Fixed¶
-
-Changed¶
+
+Changed¶
By default, semantic features are skipped in scaling, as the robust scaler
cannot deal well with categorical variables.
Wrapped scalers in single WORC scaler object to allow above for all scalers.
-
-
-3.3.2 - 2020-08-19¶
-
-Fixed¶
+
+3.3.2 - 2020-08-19¶
+
+Fixed¶
Bug in fit and score when using scaling: was incorrectly parsed as string
and always set to None.
Fixed
Typo in configuration documentation.
-
-Added¶
+
+Added¶
New type of scaler (robust z-scoring)
Resampling of image and mask in preprocessing (preprocessing and segmentix
nodes)
-
-
-3.3.1 - 2020-07-31¶
-
-Changed¶
+
+3.3.1 - 2020-07-31¶
+
+Changed¶
-
-
-3.3.0 - 2020-07-28¶
-
-Added¶
+
+3.3.0 - 2020-07-28¶
+
+Added¶
Graphviz vizualization of network is now nicely grouped.
Properly integrated ObjectSampler: various resampling options now available.
Added
FAQ version to documentation
-
-Changed¶
+
+Changed¶
Upgraded to new versions of sklearn (0.23.1) and imbalanced learn (0.7.0)
Some defaults, based on computation time.
ChangedL1 penalty does not work with new standard LR solver. Removed L1 penalty.
-
-
-3.2.2 - 2020-07-14¶
-
-Added¶
+
+3.2.2 - 2020-07-14¶
+
+Added¶
In classify node, when using temporary saves, start from where
the process previously stopped instead of from the beginning.
Imputation to ComBat.
-
-Changed¶
+
+Changed¶
-
-
-3.2.1 - 2020-07-02¶
-
-Added¶
+
+3.2.1 - 2020-07-02¶
+
+Added¶
Major documentation update.
-
-Changed¶
+
+Changed¶
-
-
-3.2.0 - 2020-06-26¶
-
-Added¶
+
+3.2.0 - 2020-06-26¶
+
+Added¶
Labelprocessing can now also handle having patient ID in the feature files.
Was required for ComBat.
-
-Changed¶
+
+Changed¶
Output of plot_SVM function is better ordered.
Several defaults, as we now have PyRadiomics fully embedded, resulting in
@@ -653,8 +674,8 @@
ChangedNo more overrides for the full config, as the default now is the full config.
-
-
-3.1.4 - 2020-05-26¶
-
-Added¶
+
+3.1.4 - 2020-05-26¶
+
+Added¶
Catch error if number of segmentations supplied does not match number of
images.
Added
Combat: in WORK workflow.
-
-Changed¶
+
+Changed¶
Resampling of objects is now after feature selection.
Made plot_SVM function more memory efficient.
ChangedSegmentix tool is cleaned up. Segmentix script is moved to processing.
-
-
-3.1.3 - 2020-01-24¶
-
-Added¶
+
+3.1.3 - 2020-01-24¶
+
+Added¶
Some options for the plot_images slicer function.
Validators to check your inputs before executing experiment.
Added
Error when config file cannot be found.
-
-Changed¶
+
+Changed¶
Preprocessor slows down progress and is not always neccesary. Made it optional.
Moved the preprocessor to the SearchCV script to do once on the training set,
@@ -755,18 +776,18 @@
ChangedJoblib now uses by default only 1 core and threading backend.
-
-Fixed¶
+
+Fixed¶
Bug in patient naming of plotting function: if ensembling was done in training,
do not re-ensemble.
-
-3.1.2 - 2019-12-09¶
-
-Added¶
+
+3.1.2 - 2019-12-09¶
+
+Added¶
Support for Oncoradiomics RadiomiX tool
Groupwise Search includes GLDZM, Fractal, location, NGTDM, NGLDM, wavelet,
@@ -776,38 +797,38 @@
Added
are ran. Mostly to detect possible faults/errors in the data.
-
-Changed¶
+
+Changed¶
On runtime, copy config.d file if it does not exist yet.
-
-Fixed¶
+
+Fixed¶
KNN imputation gave an error if >80% of the feature values were missing.
Added preprocessing function to remove these features.
-