错误：__ init __（）获得了意外的关键字参数“ n_splits”

Question

我将针对加利福尼亚住房数据集（来源：https://www.dcc.fc.up.pt/~ltorgo/Regression/cal_housing.html）执行ShuffleSplit()方法以适应SGD回归。
但是，应用方法时会发生“ n_splits”错误。
代码如下：

from sklearn import cross_validation, grid_search, linear_model, metrics  
import numpy as np  
import pandas as pd


from sklearn.preprocessing import scale
from sklearn.cross_validation import ShuffleSplit


housing_data = pd.read_csv('cal_housing.csv', header = 0, sep = ',')
housing_data.fillna(housing_data.mean(), inplace=True)
df=pd.get_dummies(housing_data)


y_target = housing_data['median_house_value'].values
x_features = housing_data.drop(['median_house_value'], axis = 1)

from sklearn.cross_validation import train_test_split
from sklearn import model_selection

train_x, test_x, train_y, test_y = model_selection.train_test_split(x_features, y_target, test_size=0.2, random_state=4)
reg = linear_model.SGDRegressor(random_state=0)
cv = ShuffleSplit(n_splits = 10, test_size = 0.2, random_state = 0)

错误如下：

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-22-8f8760b04f8c> in <module>()
----> 1 cv = ShuffleSplit(n_splits = 10, test_size = 0.2, random_state = 0)

TypeError: __init__() got an unexpected keyword argument 'n_splits'

我用 0.18版本更新了scikit-learn。

Anaconda版本： 4.5.8

请您提供有关此问题的建议？

Answer 1

您正在混淆两个不同的模块。

在0.18之前，cross_validation用于ShuffleSplit。因此，n_splits不存在。 n用于定义拆分次数

但是，由于您现在已更新到0.18，因此不推荐使用cross_validation和grid_search来支持model_selection。

docs here中已提及，这些模块将从版本0.20中删除

所以代替这个：

from sklearn.cross_validation import ShuffleSplit
from sklearn.cross_validation import train_test_split

执行以下操作：

from sklearn.model_selection import ShuffleSplit
fro

m sklearn.model_selection导入train_test_split

然后您可以使用n_splits。

cv = ShuffleSplit(n_splits = 10, test_size = 0.2, random_state = 0)