ROC.py 文件源码

def addFold(self, fold_id, true_labels, predicted_proba, predicted_scores):
        if len(true_labels) == 0:
            return
        if self.probabilist_model:
            scores = predicted_proba
        else:
            scores = predicted_scores
        fpr, tpr, thresholds = roc_curve(true_labels, scores)
        self.mean_tpr += interp(self.mean_fpr, fpr, tpr)
        self.thresholds = interp(self.mean_fpr, fpr, thresholds)
        self.mean_tpr[0] = 0.0
        self.thresholds[0] = 1.0
        self.thresholds[-1] = 0.0
        roc_auc = auc(fpr, tpr)
        if self.num_folds > 1:
            self.ax1.plot(fpr, tpr, lw = 1,
                    label = 'ROC fold %d (area = %0.2f)' % (fold_id, roc_auc))
        else:
            self.ax1.plot(fpr, tpr, lw = 3,
                    color = colors_tools.getLabelColor('all'),
                    label = 'ROC (area = %0.2f)' % (roc_auc))