from sklearn.model_selection import train_test_split
时间: 2023-11-06 07:00:26 浏览: 40
The `train_test_split` function is a function from the `sklearn.model_selection` module in scikit-learn, which is used to split an input dataset randomly into training and testing subsets.
The function takes in the following parameters:
- `X`: The input dataset (array-like, sparse matrix, or Pandas DataFrame) containing the features.
- `y`: The target variable (array-like or Pandas Series) containing the labels.
- `test_size`: The proportion of the dataset to include in the test split (default=0.25).
- `random_state`: The seed used by the random number generator (default=None).
- `shuffle`: Whether or not to shuffle the data before splitting (default=True).
The function returns four outputs:
- `X_train`: The training subset of the input dataset.
- `X_test`: The testing subset of the input dataset.
- `y_train`: The training subset of the target variable.
- `y_test`: The testing subset of the target variable.