LinearL1CD

class lightautoml.ml_algo.linear_sklearn.LinearL1CD(default_params=None, freeze_defaults=True, timer=None, optimization_search_space={})[source]

Bases: TabularMLAlgo

Coordinate descent based on sklearn implementation.

init_params_on_input(train_valid_iterator)[source]

Get model parameters depending on dataset parameters.

Parameters:: train_valid_iterator (TrainValidIterator) – Classic cv-iterator.
Return type:: dict
Returns:: Parameters of model.

fit_predict_single_fold(train, valid)[source]

Train on train dataset and predict on holdout dataset.

Parameters:

train (Union[NumpyDataset, CSRSparseDataset, PandasDataset]) – Train Dataset.
valid (Union[NumpyDataset, CSRSparseDataset, PandasDataset]) – Validation Dataset.

Return type:

Tuple[Union[LogisticRegression, ElasticNet, Lasso], ndarray]

Returns:

Target predictions for valid dataset.

predict_single_fold(model, dataset)[source]

Implements prediction on single fold.

Parameters:

model (Union[LogisticRegression, ElasticNet, Lasso]) – Model uses to predict.
dataset (Union[NumpyDataset, CSRSparseDataset, PandasDataset]) – Dataset used for prediction.

Return type:

ndarray

Returns:

Predictions for input dataset.