SubgroupVarianceCalculator

Calculator that calculates variance metrics for subgroups.

Parameters

• X_test (pandas.core.frame.DataFrame)

  Processed features test set

• y_test (pandas.core.frame.DataFrame)

  Targets test set

• sensitive_attributes_dct (dict)

  A dictionary where keys are sensitive attributes names (including attributes intersections), and values are privilege values for these subgroups

• test_protected_groups – defaults to None

  A dictionary where keys are sensitive attributes, and values input dataset rows that are correspondent to these sensitive attributes.

• computation_mode (str) – defaults to None

  [Optional] A non-default mode for metrics computation. Should be included in the ComputationMode enum.

• with_predict_proba (bool) – defaults to True

  [Optional] A flag if model can return probabilities for its predictions. If no, only metrics based on labels (not labels and probabilities) will be computed.

Methods

compute_subgroup_metrics

Compute variance metrics for subgroups.

Return a dict of dicts where key is 'overall' or a subgroup name, and value is a dict of metrics for this subgroup.

Parameters

• y_preds
• models_predictions (dict)
• save_results (bool)
• result_filename (str) – defaults to None
• save_dir_path (str) – defaults to None

save_metrics_to_file

Parameters

• result_filename (str)
• save_dir_path (str)

set_overall_variance_metrics