def show_classifier_metrics(test_list, prediction_list):
privileged_groups = [{'sex': 1}]
unprivileged_groups = [{'sex': 0}]
counter = 1
for test_, pred_ in zip(test_list, prediction_list):
display(Markdown("#### Model {} dataset metrics".format(counter)))
model_metric = ClassificationMetric(
test_,
pred_,
unprivileged_groups=unprivileged_groups,
privileged_groups=privileged_groups)
ex_model_metric = MetricTextExplainer(model_metric)
print(ex_model_metric.average_odds_difference())
print(
'Difference in Recall between Unprivileged and Privileged: {:.3f}'.
format(model_metric.equal_opportunity_difference()))
print(
'Difference in Precision between Unprivileged and Privileged: {:.3f}.'
.format(
model_metric.precision(privileged=False) -
model_metric.precision(privileged=True)))
counter += 1
def get_classifier_metrics(test_list, prediction_list):
privileged_groups = [{'sex': 1}]
unprivileged_groups = [{'sex': 0}]
acc_list = []
bal_acc_list = []
avg_odds_list = []
recall_diff_list = []
precision_diff_list = []
for test_, pred_ in zip(test_list, prediction_list):
model_metric = ClassificationMetric(
test_,
pred_,
unprivileged_groups=unprivileged_groups,
privileged_groups=privileged_groups)
acc_list.append(model_metric.accuracy().round(3))
bal_acc_list.append(((model_metric.true_positive_rate() +
model_metric.true_negative_rate()) / 2).round(3))
avg_odds_list.append(model_metric.average_odds_difference().round(3))
recall_diff_list.append(
model_metric.equal_opportunity_difference().round(3))
precision_diff_list.append(
(model_metric.precision(privileged=False) -
model_metric.precision(privileged=True)).round(3))
return acc_list, bal_acc_list, avg_odds_list, recall_diff_list, precision_diff_list
