create_validation_iterator
- lightautoml.validation.utils.create_validation_iterator(train, valid=None, n_folds=None, cv_iter=None)[source]
Creates train-validation iterator.
If train is one of common datasets types (
PandasDataset
,NumpyDataset
,CSRSparseDataset
) theget_numpy_iterator
will be used. Else if validation dataset is defined, the holdout-iterator will be used. Else the dummy iterator will be used.- Parameters
train (
LAMLDataset
) – Dataset to train.valid (
Optional
[LAMLDataset
]) – Optional dataset for validate.n_folds (
Optional
[int
]) – maximum number of folds to iterate. IfNone
- iterate through all folds.cv_iter (
Optional
[Callable
]) – Takes dataset as input and return an iterator of indexes of train/valid for train dataset.
- Return type
- Returns
New iterator.