TrainValidIterator
- class lightautoml.validation.base.TrainValidIterator(train, **kwargs)[source]
Bases:
object
Abstract class to train/validation iteration.
Train/valid iterator: should implement __iter__ and __next__ for using in ml_pipeline.
- property features
Dataset features names.
- Returns
List of features names.
- __init__(train, **kwargs)[source]
- Parameters
train (~Dataset) – Train dataset.
**kwargs – Key-word parameters.
- apply_feature_pipeline(features_pipeline)[source]
Apply features pipeline on train data.
- Parameters
features_pipeline (
FeaturesPipeline
) – Composite transformation of features.- Return type
- Returns
Copy of object with transformed features.
- apply_selector(selector)[source]
Select features on train data.
Check if selector is fitted. If not - fit and then perform selection. If fitted, check if it’s ok to apply.
- Parameters
selector – Uses for feature selection.
- Return type
- Returns
Dataset with selected features.