Fairness Evaluation Metrics with Confidence Intervals


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Documentation for package ‘fairmetrics’ version 1.0.1

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eval_acc_parity Examine Accuracy Parity of a Model
eval_bs_parity Examine Brier Score Parity of a Model
eval_cond_acc_equality Examine Conditional Use Accuracy Equality of a Model
eval_cond_stats_parity Examine Conditional Statistical Parity of a Model
eval_eq_odds Examine Equalized Odds of a Predictive Model
eval_eq_opp Evaluate Equal Opportunity Compliance of a Predictive Model
eval_neg_class_bal Examine Balance for Negative Class of a Model
eval_neg_pred_parity Examine Negative Predictive Parity of a Model
eval_pos_class_bal Examine Balance for the Positive Class of a Model
eval_pos_pred_parity Examine Positive Predictive Parity of a Model
eval_pred_equality Examine Predictive Equality of a Model
eval_stats_parity Examine Statistical Parity of a Model
eval_treatment_equality Examine Treatment Equality of a Model
get_all_metrics Calculate the all metrics at once
get_fairness_metrics Compute Fairness Metrics for Binary Classification
mimic Clinical data from the MIMIC-II database for a case study on indwelling arterial catheters
mimic_preprocessed Preprocessed Clinical Data from the MIMIC-II Database