# skfolio.model_selection.BaseCombinatorialCV ### *class* skfolio.model_selection.BaseCombinatorialCV Base class for all combinatorial cross-validators. Implementations must define `split` or `get_path_ids`. ### Methods | [`get_path_ids`](#skfolio.model_selection.BaseCombinatorialCV.get_path_ids)() | Return the path id of each test sets in each split. | |-------------------------------------------------------------------|------------------------------------------------------------| | [`split`](#skfolio.model_selection.BaseCombinatorialCV.split)(X[, y]) | Generate indices to split data into training and test set. | #### *abstractmethod* get_path_ids() Return the path id of each test sets in each split. #### *abstractmethod* split(X, y=None) Generate indices to split data into training and test set. * **Parameters:** **X** *array-like of shape (n_samples, n_features)* : Training data, where `n_samples` is the number of samples and `n_features` is the number of features. **y** *array-like of shape (n_samples,), optional* : The (multi-)target variable. * **Yields:** **train** *ndarray* : The training set indices for that split. **test** *list[ndarray]* : The testing set indices of each test group for that split.