Pratik-model 0.0.9

This package directly gives you output performance on 13 different algorithms

- The best thing about this package is that you don’t have to train and predict every 

classification or regression algorithm to check performance. 

- This package directly gives you output performance on 13 different algorithms.



For Classification

from Pratik_model import smart_classifier



model = smart_classifier(x,y)

model.accuracy_score()

model.classification_report()

model.confusion_matrix()

model.cross_validation()

model.mean_absolute_error()

model.precision_score()

model.recall_score()

model.mean_absolute_error()

model.mean_absolute_error()

model.mean_squared_error()

model.cross_validation()



For Regression 

from Pratik_model import smart_regressor



model=smart_regressor(x,y)

model.r2_score()

model.mean_absolute_error()

model.mean_absolute_error()

model.mean_squared_error()

model.cross_validation()

model.overfitting()





For more details check Source code .



First Release

0.0.2 (29/3/2022)



Thank You!!.

License-File: LICENSE.txt