Method _eval_metrics

catboost/python-package/catboost/core.py:3212–3232

(self, data, metrics, ntree_start, ntree_end, eval_period, thread_count, res_dir, tmp_dir, plot, plot_file, log_cout=None, log_cerr=None)

        return self._get_embedding_feature_indices()

    def _eval_metrics(self, data, metrics, ntree_start, ntree_end, eval_period, thread_count, res_dir, tmp_dir, plot, plot_file, log_cout=None, log_cerr=None):
        if not self.is_fitted():
            raise CatBoostError("There is no trained model to evaluate metrics on. Use fit() to train model. Then call this method.")
        if not isinstance(data, Pool):
            raise CatBoostError("Invalid data type={}, must be catboost.Pool.".format(type(data)))
        if data.is_empty_:
            raise CatBoostError("Data is empty.")
        if not isinstance(metrics, ARRAY_TYPES) and not isinstance(metrics, STRING_TYPES) and not isinstance(metrics, BuiltinMetric):
            raise CatBoostError("Invalid metrics type={}, must be array like, str or one of builtin catboost.metrics.* class instances.".format(type(metrics)))
        if not all(map(lambda metric: isinstance(metric, string_types) or isinstance(metric, BuiltinMetric), metrics)):
            raise CatBoostError("Invalid metric type: must be str or one of builtin catboost.metrics.* class instances.")
        if tmp_dir is None:
            tmp_dir = tempfile.mkdtemp()

        if isinstance(metrics, STRING_TYPES) or isinstance(metrics, BuiltinMetric):
            metrics = [metrics]
        metrics = stringify_builtin_metrics_list(metrics)
        with log_fixup(log_cout, log_cerr), plot_wrapper(plot, plot_file, 'Eval metrics plot', [res_dir]):
            metrics_score, metric_names = self._base_eval_metrics(data, metrics, ntree_start, ntree_end, eval_period, thread_count, res_dir, tmp_dir)

        return dict(zip(metric_names, metrics_score))

    def eval_metrics(self, data, metrics, ntree_start=0, ntree_end=0, eval_period=1, thread_count=-1, tmp_dir=None, plot=False, plot_file=None, log_cout=None, log_cerr=None):
        """