BinaryPerfIndicators.py 文件源码

def addNonProbabilistFold(self, fold_id, true_labels, predicted_labels):
        precision, recall, f_score, _ = precision_recall_fscore_support(true_labels, predicted_labels,
                                                                        average = 'binary')
        accuracy = accuracy_score(true_labels, predicted_labels)
        if len(predicted_labels) == 0:
                fp = 0
                tn = 0
        else:
            conf_matrix = confusion_matrix(true_labels, predicted_labels, [True, False])
            fp = conf_matrix[1][0]
            tn = conf_matrix[1][1]
        fp_tn = fp + tn
        if fp_tn == 0:
            false_alarm_rate = 0
        else:
            false_alarm_rate = fp / (fp + tn)
        self.fold_perf[fold_id, :] = [precision, recall, false_alarm_rate, f_score, accuracy]