Metrics
holisticai.bias.metrics is a python module measuring bias in algorithms. Metrics are included for classification, regression, clustering, recommender and multiclass tasks.
Binary Classification
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ABROCA (area between roc curves). |
Accuracy Difference. |
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Average Odds Difference. |
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Classification bias metrics batch computation. |
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Cohen D. |
Disparate Impact. |
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Equality of opportunity difference. |
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False negative Rate difference. |
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False positive rate difference. |
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Four Fifths. |
Statistical parity. |
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True negative Rate difference. |
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Z Test (Difference). |
Z Test (Ratio). |
Multiclass Classification
Multiclass Accuracy Matrix. |
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Confusion Matrix. |
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Confusion Tensor. |
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Frequency Matrix. |
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Multiclass Average Odds. |
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Multiclass bias metrics batch computation. |
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Multiclass Equality of Opportunity. |
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Multiclass statistical parity. |
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Multiclass True Rates. |
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Multiclass Precision Matrix. |
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Multiclass Recall Matrix. |
Regression
Average Score Difference. |
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Correlation difference. |
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Disparate Impact quantile (Regression version). |
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MAE ratio |
Max absolute statistical parity. |
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No disparate impact level. |
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Regression bias metrics batch computation |
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RMSE ratio. |
Statistical parity (AUC). |
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Statistical Parity quantile (Regression version). |
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ZScore Difference. |
Clustering
Cluster Balance. |
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Minority Cluster Distribution Entropy. |
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Cluster Distribution KL. |
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Cluster Distribution Total Variation. |
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Clustering bias metrics batch computation. |
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Minimum Cluster Ratio. |
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Silhouette Difference. |
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Social Fairness Ratio. |
Recommender
Aggregate Diversity. |
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Average f1 ratio |
Average precision ratio |
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Average recall ratio |
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Average Recommendation Popularity. |
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Exposure Entropy. |
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Exposure KL Divergence. |
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Exposure Total Variation. |
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GINI index. |
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Mean Absolute Deviation. |
Recommender bias metrics batch computation. |
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Recommender MAE ratio. |
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Recommender RMSE ratio. |