HoldoutIterator
- class lightautoml.validation.base.HoldoutIterator(train, valid)[source]
Bases:
TrainValidIterator
Iterator for classic holdout - just predefined train and valid samples.
- __init__(train, valid)[source]
Create iterator.
- Parameters:
train (
LAMLDataset
) – Dataset of train data.valid (
LAMLDataset
) – Dataset of valid data.
- get_validation_data()[source]
Just get validation sample.
- Return type:
- Returns:
Whole validation dataset.
- apply_feature_pipeline(features_pipeline)[source]
Inplace apply features pipeline to iterator components.
- Parameters:
features_pipeline (
FeaturesPipeline
) – Features pipeline to apply.- Return type:
- Returns:
New iterator.
- apply_selector(selector)[source]
Same as for basic class, but also apply to validation.
- Parameters:
selector – Uses for feature selection.
- Return type:
- Returns:
New iterator.