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,
            }
        }
def results_class_wise_average_metrics ( self ) : 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