util.py 文件源码

def roc(y_true, y_pred, classes=[0, 1, 2, 3, 4]):
    y_true = label_binarize(y_true, classes=classes)
    y_pred = label_binarize(y_pred, classes=classes)
    n_classes = len(classes)
    fpr = dict()
    tpr = dict()
    roc_auc = dict()
    for i in range(n_classes):
        fpr[i], tpr[i], _ = roc_curve(y_true[:, i], y_pred[:, i])
        roc_auc[i] = auc(fpr[i], tpr[i])

    # Compute micro-average ROC curve and ROC area
    fpr["micro"], tpr["micro"], _ = roc_curve(y_true.ravel(), y_pred.ravel())
    roc_auc["micro"] = auc(fpr["micro"], tpr["micro"])
    return roc_auc