def results_class_wise_average_metrics(self):
        """Class-wise averaged metrics

        Returns
        -------
        dict
            results in a dictionary format

        """

        class_wise_results = self.results_class_wise_metrics()

        class_wise_eer = []
        class_wise_fmeasure = []
        class_wise_precision = []
        class_wise_recall = []

        for class_label in class_wise_results:
            if class_wise_results[class_label]['eer']['eer'] is not None:
                class_wise_eer.append(class_wise_results[class_label]['eer']['eer'])

            if class_wise_results[class_label]['f_measure']['f_measure'] is not None:
                class_wise_fmeasure.append(class_wise_results[class_label]['f_measure']['f_measure'])
                class_wise_precision.append(class_wise_results[class_label]['f_measure']['precision'])
                class_wise_recall.append(class_wise_results[class_label]['f_measure']['recall'])

        if class_wise_eer:
            eer = float(numpy.nanmean(class_wise_eer))

        else:
            eer = None

        if class_wise_fmeasure:
            f_measure = float(numpy.nanmean(class_wise_fmeasure))

        else:
            f_measure = None

        if class_wise_precision:
            precision = float(numpy.nanmean(class_wise_precision))

        else:
            precision = None

        if class_wise_recall:
            recall = float(numpy.nanmean(class_wise_recall))

        else:
            recall = None

        return {
            'eer': {
                'eer': eer
            },
            'f_measure': {
                'f_measure': f_measure,
                'precision': precision,
                'recall': recall,
            }
        }
Class-wise averaged metrics

        Returns
        -------
        dict
            results in a dictionary format