Function _test_generated_metrics

catboost/python-package/ut/medium/test.py:2672–2688

(loss_function, train_pool, test_pool, metrics, task)

def _test_generated_metrics(loss_function, train_pool, test_pool, metrics, task):
    model = CatBoost({'loss_function': loss_function, 'iterations': 50})
    model.fit(train_pool, eval_set=test_pool)

    # text description metrics
    td_results = model.eval_metrics(test_pool, list(metrics.keys()))
    # instances of autogenerated metric classes
    ag_results = model.eval_metrics(test_pool, list(metrics.values()))

    for metric in metrics:
        assert np.allclose(td_results[metric], ag_results[metric]), "Different results for {}".format(metric)

    if task not in ("ranking", "multiclassification", "multiregression", "survival_regression"):
        preds = model.predict(test_pool, prediction_type='RawFormulaVal')
        for metric, metric_obj in metrics.items():
            score = metric_obj.eval(test_pool.get_label(), preds)[0]
            assert np.abs(td_results[metric][-1] - score) < 1e-6, "Eval metric results differ for {}".format(metric)


def test_f1_vs_fbeta():