ae5602d3d008cc8b290b32e380fb72ae8fb53bd7,enso/metrics/basic_classification.py,RocAuc,evaluate,#RocAuc#Any#Any#,11

Before Change

    def evaluate(self, ground_truth, result):
        Return AUC metric.
        classwise_auc = {}
        binary_labels = labels_to_binary(ground_truth)
        for column in result.columns.values:
            classwise_auc[column] = roc_auc_score(binary_labels[column], result[column])
        return classwise_auc

After Change

        Return AUC metric.
        binary_labels = labels_to_binary(ground_truth)
        binary_labels = np.hstack([binary_labels[column].values.reshape(-1, 1) for column in result.columns])
        predicted_labels = np.hstack([result[column].values.reshape(-1, 1) for column in result.columns])
        return log_loss(binary_labels, predicted_labels)

Instances