get_numpy_iterator
- lightautoml.validation.np_iterators.get_numpy_iterator(train, valid=None, n_folds=None, iterator=None)[source]
Get iterator for np/sparse dataset.
If valid is defined, other parameters are ignored. Else if iterator is defined n_folds is ignored.
Else if n_folds is defined iterator will be created by folds index. Else
DummyIterator
- (train, train) will be created.- Parameters:
train (
Union
[CSRSparseDataset
,NumpyDataset
,PandasDataset
]) –LAMLDataset
to train.valid (
Union
[CSRSparseDataset
,NumpyDataset
,PandasDataset
,None
]) – OptionalLAMLDataset
for validate.n_folds (
Optional
[int
]) – maximum number of folds to iterate. IfNone
- iterate through all folds.iterator (
Optional
[Iterable
[Tuple
[Sequence
,Sequence
]]]) – Takes dataset as input and return an iterator of indexes of train/valid for train dataset.
- Return type:
Union
[FoldsIterator
,HoldoutIterator
,CustomIterator
,DummyIterator
]- Returns:
new train-validation iterator.