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Us","<no title>","fairlearn.adversarial.AdversarialFairnessClassifier","fairlearn.adversarial.AdversarialFairnessRegressor","fairlearn.datasets.fetch_acs_income","fairlearn.datasets.fetch_adult","fairlearn.datasets.fetch_bank_marketing","fairlearn.datasets.fetch_boston","fairlearn.datasets.fetch_credit_card","fairlearn.datasets.fetch_diabetes_hospital","fairlearn.metrics.MetricFrame","fairlearn.metrics._plotter.plot_metric_frame","fairlearn.metrics.count","fairlearn.metrics.demographic_parity_difference","fairlearn.metrics.demographic_parity_ratio","fairlearn.metrics.equalized_odds_difference","fairlearn.metrics.equalized_odds_ratio","fairlearn.metrics.false_negative_rate","fairlearn.metrics.false_positive_rate","fairlearn.metrics.make_derived_metric","fairlearn.metrics.mean_prediction","fairlearn.metrics.plot_model_comparison","fairlearn.metrics.selection_rate","fairlearn.metrics.true_negative_rate","fairlearn.metrics.true_positive_rate","fairlearn.postprocessing.ThresholdOptimizer","fairlearn.postprocessing.plot_threshold_optimizer","fairlearn.preprocessing.CorrelationRemover","fairlearn.reductions.AbsoluteLoss","fairlearn.reductions.BoundedGroupLoss","fairlearn.reductions.ClassificationMoment","fairlearn.reductions.DemographicParity","fairlearn.reductions.EqualizedOdds","fairlearn.reductions.ErrorRate","fairlearn.reductions.ErrorRateParity","fairlearn.reductions.ExponentiatedGradient","fairlearn.reductions.FalsePositiveRateParity","fairlearn.reductions.GridSearch","fairlearn.reductions.LossMoment","fairlearn.reductions.Moment","fairlearn.reductions.SquareLoss","fairlearn.reductions.TruePositiveRateParity","fairlearn.reductions.UtilityParity","fairlearn.reductions.ZeroOneLoss","API Docs","Example Notebooks","CorrelationRemover visualization","Credit Loan Decisions","GridSearch with Census Data","Making Derived Metrics","MetricFrame: Beyond Binary Classification","Passing pipelines to mitigation techniques","Metrics with Multiple Features","Plotting Metrics with Errors","MetricFrame visualizations","Selection rates in census dataset","Computation times","Contributing code","Contributing documentation","Contributing example notebooks","Development process","API and design proposals","Fairlearn Repository Overview","How to talk and write about fairness in AI","Contributor Guide","Release Process","Ways to contribute","Frequently asked questions","Table of Contents","Get Started","Advanced Usage of MetricFrame","Common fairness metrics","Defining custom fairness metrics","Assessment","Intersecting Groups","Performing a Fairness Assessment","Plotting","ACSIncome","Adult Census Dataset","Revisiting the Boston Housing Dataset","Diabetes 130-Hospitals Dataset","Datasets","Fairness in Machine Learning","Further Resources","User Guide","Installation and version guide","Installation Guide","v0.1","v0.2.0","v0.3.0","v0.4.0","v0.4.1","v0.4.2","v0.4.3","v0.4.4","v0.4.5","v0.4.6","v0.5.0","v0.6.0","v0.6.1","v0.6.2","v0.7.0","v0.8.0","v0.9.0","Version guide","Adversarial 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