Metadata-Version: 1.1
Name: BinaryClassificationMetrics
Version: 0.0.5
Summary: This package contains various binary classification metric methods.
Home-page: https://github.com/VarunV991/Binary-Classification-Metrics
Author: Varun V
Author-email: varunofficial99@gmail.com
License: MIT
Download-URL: https://github.com/VarunV991/Binary-Classification-Metrics/archive/v0.0.3.tar.gz
Description: Binary Classification Metrics
        
        This package contains various binary classification methods. The methods included are as follows:
        
        1. Precision Score - precision_score(predicted,actual)
        2. Recall Score - recall_score(predicted,actual)
        3. Selectivity or True Negative Rate - true_negative_rate(predicted,actual)
        4. Negative Predictive Value - negative_predictive_value(predicted,actual)
        5. Miss Rate or False Negative Rate - miss_rate(predicted,actual)
        6. Fall Out or False Positive Rate - fall_out_score(predicted,actual)
        7. False Discovery Rate - false_discovery_rate(predicted,actual)
        8. False Omission Rate - false_omission_rate(predicted,actual)
        9. Weighted Average Precision Score - weighted_avg_precision_score(predicted,actual)
        10. Weighted Average Recall Score - weighted_avg_recall_score(predicted,actual)
        11. Confusion Matrix - confusion_matrix(predicted,actual) - Return False Pos,False Neg,True Pos,True Neg
        
        * The two arguments are the predicted classes and actual classes of the classification.
        * Higher Class Number equates to the positive label.
Keywords: binary-classification,metrics
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
