ENH: Add confusion_matrix_statistics function in contingency_tables #9118
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NumPy's guide.
This commit generates classification performance metrics using square tables. The metrics include Accuracy, No Information Rate, Kappa, Sensitivity, Specificity, Positive Predictive Value, Negative Predictive Value, Balanced Accuracy, and F1. The code draws inspiration from Caret package in R
The overall metrics are structured in a dictionary.
The class-specific metrics output is structured in rows representing different metrics and columns representing different classes (class 1, class 2, class 3, class 4).
The test values are verified with confusionMatrix function in Caret package in R.