sklearn.cross_validation安装

sklearn.cross_validation 已经不再被支持，建议使用 model_selection 模块中的 train_test_split 和 KFold 等函数来进行交叉验证。

安装方式：使用 pip 安装 scikit-learn 即可。

在命令行输入：

pip install -U scikit-learn

也可以使用 conda 安装

conda install scikit-learn

如果你已经安装了 scikit-learn ，可以使用下面的命令来更新它

pip install --upgrade scikit-learn

相关问题

sklearn.cross_validation

The `sklearn.cross_validation` module is a deprecated module in Scikit-learn version 0.20. It was used earlier for cross-validation methods, but now it has been moved to the `sklearn.model_selection` module.

The `cross_validation` module provides tools for splitting datasets into training and testing sets, and for evaluating the performance of a machine learning model using cross-validation techniques. It includes functions such as `train_test_split`, `KFold`, `StratifiedKFold`, and `cross_val_score`.

`train_test_split` function is used to split the dataset into training and testing sets. `KFold` and `StratifiedKFold` are used to create cross-validation folds for training and testing the machine learning model. `cross_val_score` function is used to evaluate the performance of a machine learning model using cross-validation.

The `cross_validation` module is still available in Scikit-learn, but it is recommended to use the `model_selection` module instead.

sklearn.cross_validation报错

sklearn.cross_validation报错是指在使用scikit-learn库中的交叉验证模块时出现了错误。具体的错误信息需要根据具体的情况来分析，可能是参数设置不正确、数据格式不符合要求、模型选择不当等原因导致的。需要仔细查看错误信息并进行相应的调整和修正。