python模型训练报错

Classify_result=[]
names=[]
prediction=[]
for name,classifier in Classifiers:
    classifier=classifier
    classifier.fit(x_train,y_train)
    #classifier.Imputer().fit_transform(x_train,y_train)
    y_pred=classifier.predict(x_test)
    recall=recall_score(y_test,y_pred)
    precision=precision_score(y_test,y_pred)
    f1score = f1_score(y_test, y_pred)
    class_eva=pd.DataFrame([recall,precision,f1score])
    Classify_result.append(class_eva)
    name=pd.Series(name)
    names.append(name)
    y_pred=pd.Series(y_pred)
    prediction.append(y_pred)

开始报的这个错误，按照网上说的方法修改后又报新的错误。

ValueError: Input contains NaN, infinity or a value too large for dtype('float32').

新修改的代码：

Classify_result=[]
names=[]
prediction=[]
for name,classifier in Classifiers:
    classifier=classifier
    #classifier.fit(x_train,y_train)
    classifier.Imputer().fit_transform(x_train,y_train)
    y_pred=classifier.predict(x_test)
    recall=recall_score(y_test,y_pred)
    precision=precision_score(y_test,y_pred)
    f1score = f1_score(y_test, y_pred)
    class_eva=pd.DataFrame([recall,precision,f1score])
    Classify_result.append(class_eva)
    name=pd.Series(name)
    names.append(name)
    y_pred=pd.Series(y_pred)
    prediction.append(y_pred)

报的新错误：

AttributeError: 'RandomForestClassifier' object has no attribute 'Imputer'