def evaluation_metrics(y_true, y_pred):
    (fpr, tpr, thresholds) = roc_curve(y_true=y_true, y_score=y_pred, pos_label=1)
    auc_ = auc(fpr, tpr)
    y_pred = [(1 if (p >= 0.5) else 0) for p in y_pred]
    acc = accuracy_score(y_true=y_true, y_pred=y_pred)
    prc = precision_score(y_true=y_true, y_pred=y_pred)
    rc = recall_score(y_true=y_true, y_pred=y_pred)
    f1 = 0
    return (acc, prc, rc, f1, auc_)
def evaluation_metrics(y_true, y_pred):
    (fpr, tpr, thresholds) = roc_curve(y_true=y_true, y_score=y_pred, pos_label=1)
    auc_ = auc(fpr, tpr)
    y_pred = [(1 if (p >= 0.5) else 0) for p in y_pred]
    acc = accuracy_score(y_true=y_true, y_pred=y_pred)
    prc = precision_score(y_true=y_true, y_pred=y_pred)
    rc = recall_score(y_true=y_true, y_pred=y_pred)
    f1 = 0
    return (acc, prc, rc, f1, auc_)