问题描述
我正在看本教程：
我进入第9部分，进行了预测。在其中，有一个数据数据称为泰坦尼克号，然后使用以下方法将其分成折叠：
I got to part 9, making predictions. In there there is some data in a dataframe called titanic, which is then divided up in folds using:
# Generate cross validation folds for the titanic dataset. It return the row indices corresponding to train and test.
# We set random_state to ensure we get the same splits every time we run this.
kf = KFold(titanic.shape[0], n_folds=3, random_state=1)
I am not sure what is it exactly doing and what kind of object kf is. I tried reading the documentation but it did not help much. Also, there are three folds (n_folds=3), why is it later only accessing train and test (and how do I know they are called train and test) in this line?
for train, test in kf:
推荐答案
KFold将提供训练/测试索引，以在训练和测试集中拆分数据。它将数据集分成连续的 k 折叠（默认不改组），然后每个折叠使用一次验证集，而 k-1 剩下的褶皱形成训练集（
KFold object was moved to the sklearn.model_selection module in version 0.20. To import KFold in sklearn 0.20+ use from sklearn.model_selection import KFold. KFold current documentation source
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