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SklearnDatasetSelector.py
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SklearnDatasetSelector.py
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class SklearnDatasetSelector:
def select(self, dataset):
if dataset == 'breast_cancer':
from sklearn.datasets import load_breast_cancer ### Binary classification example sklearnDataset = load_breast_cancer() elif dataset == 'iris':
sklearn_dataset = load_breast_cancer()
elif dataset == 'iris':
from sklearn.datasets import load_iris ### Multiclass classification example
sklearn_dataset = load_iris()
elif dataset == 'boston':
from sklearn.datasets import load_boston ### Regression example
sklearn_dataset = load_boston()
else:
raise Exception('Invalid dataset: ', dataset)
self._sklearn_dataset_info_print(sklearn_dataset)
return sklearn_dataset
def _sklearn_dataset_info_print(self, sklearn_dataset):
print("============================================")
print("INFORMATION OF DATASET")
print("Feature: shape = {}\nFeature names: {}".format(sklearn_dataset.data.shape, sklearn_dataset.feature_names))
if hasattr(sklearn_dataset, 'target_names'):
print("Target: shape = {}\nTarget names: {}".format(sklearn_dataset.target.shape, sklearn_dataset.target_names))
print("============================================")