Metadata-Version: 2.1
Name: Pratik_model
Version: 0.0.9
Summary: This package directly gives you output performance on 13 different algorithms
Home-page: 
Author: pratik
Author-email: pratikvdatey@gmail.com
License: MIT
Project-URL: source_code, https://github.com/pratikdatey/Pratik_model
Keywords: Pratik_model
Classifier: Intended Audience :: Education
Classifier: Operating System :: Microsoft :: Windows :: Windows 10
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Description-Content-Type: Pratik model

- The best thing about this package is that you donâ€™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
