交叉验证

现在sklearn里面改版了，在将来的版本中将不存在cross_validation

以前的版本是：

from sklearn import cross_validation
from sklearn import datasets
iris = datasets.load_iris()
print(iris.data.shape, iris.target.shape)
# ((150, 4), (150,))
X_train, X_test, y_train, y_test = cross_validation.train_test_split(iris.data, iris.target, test_size=0.4, random_state=0)

>>> X_train.shape, y_train.shape
((90, 4), (90,))
>>> X_test.shape, y_test.shape
((60, 4), (60,))

现在的版本是：

from sklearn.model_selection import train_test_split
from sklearn import datasets

iris = datasets.load_iris()
X_train, X_test, y_train, y_test = train_test_split(iris.data, iris.target, test_size=.4, random_state=0)

 test_size是样本占比。如果是整数的话就是样本的数量。random_state是随机数的种子。