Scikit learn(Python 3.5):我是否需要导入库才能使其工作？

Question

我正在使用Python Data Science Essentials(第2版).

该书提供以下代码:

chosen_random_state = 1
X_train, X_test, y_train, y_test = cross_validation.train_test_split(X, y, test_size=0.30, ran-dom_state=chosen_random_state)
print ("(X train shape %s, X test shape %s, \ny train shape %s, y test shape %s" \
% (X_train.shape, X_test.shape, y_train.shape, y_test.shape))
h1.fit(X_train,y_train)
print (h1.score(X_test,y_test)) 

当我尝试运行它时,我收到以下错误:

-------------------------------------------------- ------------------------- NameError Traceback(最近一次调用last)in()1 chosen_random_state = 1 ----> 2 X_train,X_test, y_train,y_test = cross_validation.train_test_split(X,y,test_size = 0.30,random_state = chosen_random_state)3打印("(X列车形状%s,X测试形状%s,\n列车形状%s,y测试形状%s") %(X_train.shape,X_test.shape,y_train.shape,y_test.shape))4 h1.fit(X_train,y_train)5 print(h1.score(X_test,y_test))

NameError:未定义名称"cross_validation"

我怀疑我可能要导入一本书未提及的图书馆.我搜索了手册,但找不到这个功能.这是我需要创建的功能还是有人可以指向相关的库？

Answer 1

cross_validation子模块sklearn已弃用.您应该使用sklearn.model_selection ,而不是

from sklearn import model_selection

...
X_train, X_test, y_train, y_test = model_selection.train_test_split(X, y, test_size=0.30, ran-dom_state=chosen_random_state)
...