tabular_user_experiments.py
def compute_score_interpretability_method(features_employed_by_explainer, features_employed_black_box):
    """
    Compute the score of the explanation method based on the features employed for the explanation compared to the features truely used by the black box
    """
    precision = 0
    recall = 0
    for feature_employe in features_employed_by_explainer:
        if feature_employe in features_employed_black_box:
            precision += 1
    for feature_employe in features_employed_black_box:
        if feature_employe in features_employed_by_explainer:
            recall += 1
    return precision/len(features_employed_by_explainer), recall/len(features_employed_black_box)

    Compute the score of the explanation method based on the features employed for the explanation compared to the features truely used by the black box
    
Compute the score of the explanation method based on the features employed for the explanation compared to the features truely used by the black box
Compute the score of the explanation method based on the features employed for the explanation compared to the features truely used by the black box
def compute_score_interpretability_method(features_employed_by_explainer, features_employed_black_box):
    precision = 0
    recall = 0
    for feature_employe in features_employed_by_explainer:
        if feature_employe in features_employed_black_box:
            precision += 1
    for feature_employe in features_employed_black_box:
        if feature_employe in features_employed_by_explainer:
            recall += 1
    return precision/len(features_employed_by_explainer), recall/len(features_employed_black_box)
def compute_score_interpretability_method ( features_employed_by_explainer , features_employed_black_box ) : precision = 0 recall = 0 for feature_employe in features_employed_by_explainer : if feature_employe in features_employed_black_box : precision += 1 for feature_employe in features_employed_black_box : if feature_employe in features_employed_by_explainer : recall += 1 return precision / len ( features_employed_by_explainer ) , recall / len ( features_employed_black_box )
Compute the score of the explanation method based on the features employed for the explanation compared to the features truely used by the black box
Compute the score of the explanation method based on the features employed for the explanation compared to the features truely used by the black box
"""
    Compute the score of the explanation method based on the features employed for the explanation compared to the features truely used by the black box
    """
features_employed_by_explainer
features_employed_black_box