documentationhelp wanted
Repository-Metriken
- Stars
- (2.254 Stars)
- PR-Merge-Metriken
- (PR-Metriken ausstehend)
Beschreibung
Describe the issue linked to the documentation
The example at https://fairlearn.org/main/auto_examples/plot_grid_search_census.html is outright painful to read at the end, starting after
predictors = sweep.predictors_
and ending with the plot. We now have plot_model_comparison that can take care of all that. The filtering for non-dominated may require a little extra code, but we shouldn't have to mess around with moments like
error = ErrorRate()
error.load_data(X_train), pd.Series(Y_train), sensitive_features=A_train)
disparity = DemographicParity()
disparity.load_data(X_train), pd.Series(Y_train), sensitive_features=A_train)
errors.append(error.gamma(classifier)[0])
disparities.append(disparity.gamma(classifier).max()
Suggest a potential alternative/fix
Use
accuracy_score
and
make_derived_metric(metric=selection_rate, transform="difference")
to get the error and selection rate differences (called disparities above). Use plot_model_comparison rather than creating the plot from scratch.