Successfully solved (machine learning data segmentation problem): modulenotfounderror: no module named 'sklearn cross_ validation‘

Successfully solved （ Machine learning data segmentation problem ）：ModuleNotFoundError: No module named ‘sklearn.cross_validation’

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Error code

In machine learning , Divide the original data into “ Test set ” and “ Training set ”, Regular use sklearn.cross_validation Inside train_test_split Modules are used to split data .

My code ：

from sklearn.cross_validation import train_test_split
from sklearn.datasets import load_iris

iris = load_iris()
x_train, x_test, y_train, y_test = train_test_split(iris.data, iris.target, test_size=0.25, random_state=42)

print(" The eigenvalues of the training set ：", x_train)
print(" The eigenvalues of the test set ：", x_test)
print(" The target value of the training set ：", y_train)
print(" The target value of the test set ：", y_test)
print(" Target value shape of training set :", y_train.shape)
print(" The target value shape of the test set :", y_test.shape) 

Report the wrong result ：

    from sklearn.cross_validation import train_test_split
ModuleNotFoundError: No module named 'sklearn.cross_validation'

Solutions

Translation of error reporting content ：ModuleNotFoundError： There is no name “sklearn” Module .cross\u verification ’

Error reason ： newest sklearn Module , at present train_test_split No more cross_validation 了

resolvent

The guide package code can be changed as follows ：

from sklearn.model_selection import train_test_split