Python+Numpy:TypeError:'int'对象不可调用

我试图通过10倍交叉验证找到加性平滑的最佳平滑参数.我写了以下代码:

alphas = list(np.arange(0.0001, 1.5000, 0.0001))

#empty list that stores cv scores
cv_scores = []

#perform k fold cross validation
for alpha in alphas:
    naive_bayes = MultinomialNB(alpha=alpha)
    scores = cross_val_score(naive_bayes, x_train_counts, y_train, cv=10, scoring='accuracy')
    cv_scores.append(scores.mean())

#changing to misclassification error
MSE = [1 - x for x in cv_scores]  

#determining best alpha
optimal_alpha = alphas[MSE.index(min(MSE))]

我收到以下错误:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
 in ()
     18 
     19 #determining best alpha
---> 20 optimal_alpha = alphas[MSE.index(min(MSE))]
     21 print('\nThe optimal value of alpha is %f' % optimal_alpha)
     22 

TypeError: 'int' object is not callable

我为arange()和K(交叉验证)的不同参数值运行了相同的代码.这是我第一次遇到这个错误.为什么？

代码中的其他地方你有一些看起来像这样的东西:

 min = 10

然后你写这个:

optimal_alpha = alphas[MSE.index(min(MSE))]

因此,min()被解释为函数调用.