Metadata-Version: 2.1
Name: evaluation-metrics
Version: 0.1.0
Summary: This Package contains methods to evaluate the ML Model metrics.
Home-page: https://github.com/KSTarun/evaluation-metrics/
License: MIT
Author: KS Tarun
Author-email: kstarun27@gmail.com
Requires-Python: >=3.7,<4.0
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Requires-Dist: matplotlib (>=3.7.0,<4.0.0)
Requires-Dist: pandas (>=1.5.3,<2.0.0)
Requires-Dist: scikit-learn (>=1.2.1,<2.0.0)
Project-URL: Repository, https://github.com/KSTarun/evaluation-metrics/
Description-Content-Type: text/markdown

## A package to compute the KS Score, AUC & Gini Coefficient of the model for the given predictions

Methods
* plot_roc_curve(): Plots the ROC Curve
* compute_auc_gini(): Returns the AUC and Gini coefficient
* compute_gains_table_ks(): Computes the gains table from the provided predictions DataFrame. Returns the gains 
* table & KS value from the gains table.

