Project Scope

This Module help to select the base model over various ML Algorithms for our classification

Installation

pip3 install maxiverse (or) pip3 install maxiverse_(version)

Usage

>>> from maxiverse.classifier.evaluator import EvalModel
>>> 
>>> EvalModel._has_classifier()
# ['logreg', 'svm', 'dtree', 'rnf', 'nvbys', 'adabst', 'knn', 'xgbst']
>>> 
>>> 
>>> EvalModel(X_train, Y_train, 10)._perform_validate(['knn'])
         KNearestClassifier	Best Score
Accuracy	0.978644	    KNearest Classifier
Precision	0.992221	    KNearest Classifier
Recall	    0.964826	    KNearest Classifier
F1 Score	0.978320	    KNearest Classifier
>>> 
>>> EvalModel(X_train, Y_train, 20)._perform_validate(['knn', 'rnf'])
         KNearestClassifier	Random Forest Best Score
Accuracy	0.978644	      0.983600    RandomForest
Precision	0.992221	      0.994982    RandomForest
Recall	    0.964826	      0.972086    RandomForest
F1 Score	0.978320	      0.983391    RandomForest

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

License

MIT