python:交叉验证中的报错

 

from sklearn.model_selection import KFold
kf = KFold(len(y_train), 5, random_state=1) 
scores = []
for iteration, indices in enumerate(kf, start=1):
    X_train=X_train.reset_index(drop=True)
    y_train=y_train.reset_index(drop=True)
    lr=LR(random_state=1)
    lr.fit(X_train.iloc[indices[0],:],y_train.iloc[indices[0]].values.ravel())
    y_pred = lr.predict_proba(X_train.iloc[indices[1],:].values)[:, 1]
    score = metrics.roc_auc_score(y_train.iloc[indices[1]].values, y_pred)
    scores.append(score)
    print('迭代次数 ', iteration,': 得分 = ', score)
print('平均得分 ', np.mean(scores))

1、ModuleNotFoundError: No module named 'sklearn.cross_validation

 

          sklearn已经将cross_validation合并到model_selection

from sklearn.model_selection import KFold

2、TypeError: shuffle must be True or False; got 5

       

 

 

              添加shuffle=False，删掉第一个参数位的值

kf=KFold(5,random_state=1,shuffle=False)

             shuffle并不是必须的，可以删掉

3、TypeError: 'KFold' object is not iterable

 

 

for iteration, indices in enumerate(kf.split(y_train), start=1):