NestedTabularMLAlgo

class lightautoml.pipelines.ml.nested_ml_pipe.NestedTabularMLAlgo(ml_algo, tuner=None, refit_tuner=False, cv=5, n_folds=None)[source]

Bases: TabularMLAlgo, ImportanceEstimator

Wrapper for MLAlgo to make it trainable over nested folds.

Limitations - only for TabularMLAlgo.

property params

Parameters of ml_algo.

init_params_on_input(train_valid_iterator)[source]

Init params depending on input data.

Parameters:

train_valid_iterator (TrainValidIterator) – Iterator over input data.

Return type:

dict

Returns:

dict with model hyperparameters.

fit_predict_single_fold(train, valid)[source]

Implements training and prediction on single fold.

Parameters:
Return type:

Tuple[Any, ndarray]

Returns:

Tuple (model, predicted_values).

predict_single_fold(model, dataset)[source]

Model prediction on a dataset.

Parameters:
Return type:

ndarray

Returns:

Predictions.

get_features_score()[source]

Score of each features.

Return type:

Series

fit(train_valid)[source]

Just to be compatible with ImportanceEstimator.

Parameters:

train_valid (TrainValidIterator) – Classic cv iterator.