PyPI

.gitignore

@@ -5,3 +5,4 @@ dist/
 *egg-info*
 *__pycache__/
 *.py[cod]
+*eggs*

MANIFEST.in

@@ -0,0 +1 @@
+recursive-include data *

README.md

@@ -25,10 +25,12 @@ Feel free to [reach out](mailto:[email protected]) if you can think of w
 
 ## Usage
 ### Installation
-    $ pip install -r requirements.txt
+    $ pip install mlfs
+or
+    ```$ python setup.py install```
 
 ### Regression
-    $ python supervised_learning/linear_regression.py
+    $ python mlfs/supervised_learning/linear_regression.py
 
 <p align="center">
     <img src="http://eriklindernoren.se/images/pr4.png" width="640"\>
@@ -38,7 +40,7 @@ Feel free to [reach out](mailto:[email protected]) if you can think of w
 </p>
 
 ### Classification
-    $ python supervised_learning/multilayer_perceptron.py
+    $ python mlfs/supervised_learning/multilayer_perceptron.py
 
 <p align="center">
     <img src="http://eriklindernoren.se/images/mlp3.png" width="640">
@@ -48,7 +50,7 @@ Feel free to [reach out](mailto:[email protected]) if you can think of w
 </p>
 
 ### Clustering
-    $ python unsupervised_learning/dbscan.py
+    $ python mlfs/unsupervised_learning/dbscan.py
 
 <p align="center">
     <img src="http://eriklindernoren.se/images/dbscan3.png" width="640">
@@ -58,7 +60,7 @@ Feel free to [reach out](mailto:[email protected]) if you can think of w
 </p>
 
 ### Association Analysis
-    $ python unsupervised_learning/apriori.py 
+    $ python mlfs/unsupervised_learning/apriori.py 
     - Apriori -
     Minimum - support: 0.25, confidence: 0.8
     Transactions:
@@ -79,28 +81,28 @@ Feel free to [reach out](mailto:[email protected]) if you can think of w
 
 ## Current Implementations
 ### Supervised Learning
-- [Adaboost](supervised_learning/adaboost.py)
-- [Bayesian Regression](supervised_learning/bayesian_regression.py)
-- [Decision Tree](supervised_learning/decision_tree.py)
-- [Gradient Boosting](supervised_learning/gradient_boosting.py)
-- [K Nearest Neighbors](supervised_learning/k_nearest_neighbors.py)
-- [Linear Discriminant Analysis](supervised_learning/linear_discriminant_analysis.py)
-- [Linear Regression](supervised_learning/linear_regression.py)
-- [Logistic Regression](supervised_learning/logistic_regression.py)
-- [Multi-class Linear Discriminant Analysis](supervised_learning/multi_class_lda.py)
-- [Multilayer Perceptron](supervised_learning/multilayer_perceptron.py)
-- [Naive Bayes](supervised_learning/naive_bayes.py)
-- [Perceptron](supervised_learning/perceptron.py)
-- [Random Forest](supervised_learning/random_forest.py)
-- [Ridge Regression](supervised_learning/ridge_regression.py)
-- [Support Vector Machine](supervised_learning/support_vector_machine.py)
-- [XGBoost](supervised_learning/xgboost.py)
+- [Adaboost](mlfs/supervised_learning/adaboost.py)
+- [Bayesian Regression](mlfs/supervised_learning/bayesian_regression.py)
+- [Decision Tree](mlfs/supervised_learning/decision_tree.py)
+- [Gradient Boosting](mlfs/supervised_learning/gradient_boosting.py)
+- [K Nearest Neighbors](mlfs/supervised_learning/k_nearest_neighbors.py)
+- [Linear Discriminant Analysis](mlfs/supervised_learning/linear_discriminant_analysis.py)
+- [Linear Regression](mlfs/supervised_learning/linear_regression.py)
+- [Logistic Regression](mlfs/supervised_learning/logistic_regression.py)
+- [Multi-class Linear Discriminant Analysis](mlfs/supervised_learning/multi_class_lda.py)
+- [Multilayer Perceptron](mlfs/supervised_learning/multilayer_perceptron.py)
+- [Naive Bayes](mlfs/supervised_learning/naive_bayes.py)
+- [Perceptron](mlfs/supervised_learning/perceptron.py)
+- [Random Forest](mlfs/supervised_learning/random_forest.py)
+- [Ridge Regression](mlfs/supervised_learning/ridge_regression.py)
+- [Support Vector Machine](mlfs/supervised_learning/support_vector_machine.py)
+- [XGBoost](mlfs/supervised_learning/xgboost.py)
 
 ### Unsupervised Learning
-- [Apriori](unsupervised_learning/apriori.py)
-- [DBSCAN](unsupervised_learning/dbscan.py)
-- [FP-Growth](unsupervised_learning/fp_growth.py)
-- [Gaussian Mixture Model](unsupervised_learning/gaussian_mixture_model.py)
-- [K-Means](unsupervised_learning/k_means.py)
-- [Partitioning Around Medoids](unsupervised_learning/partitioning_around_medoids.py)
-- [Principal Component Analysis](unsupervised_learning/principal_component_analysis.py)
+- [Apriori](mlfs/unsupervised_learning/apriori.py)
+- [DBSCAN](mlfs/unsupervised_learning/dbscan.py)
+- [FP-Growth](mlfs/unsupervised_learning/fp_growth.py)
+- [Gaussian Mixture Model](mlfs/unsupervised_learning/gaussian_mixture_model.py)
+- [K-Means](mlfs/unsupervised_learning/k_means.py)
+- [Partitioning Around Medoids](mlfs/unsupervised_learning/partitioning_around_medoids.py)
+- [Principal Component Analysis](mlfs/unsupervised_learning/principal_component_analysis.py)