OneToOneTransformer

class lightautoml.transformers.text.OneToOneTransformer(default_params=None, freeze_defaults=False)[source]

Bases: TunableTransformer

Out-of-fold sgd model prediction to reduce dimension of encoded text data.

property features

Features list.

init_params_on_input(dataset)[source]

Get model parameters depending on dataset parameters.

Parameters:

dataset (Union[NumpyDataset, PandasDataset]) – NumpyOrPandas.

Return type:

dict

Returns:

Parameters of model.

fit(dataset)[source]

Apply fit transform.

Parameters:

dataset (Union[NumpyDataset, PandasDataset]) – Pandas or Numpy dataset of encoded text features.

Returns:

self.

fit_transform(dataset)[source]

Fit and predict out-of-fold sgd model.

Parameters:

dataset (Union[NumpyDataset, PandasDataset]) – Pandas or Numpy dataset of encoded text features.

Return type:

NumpyDataset

Returns:

Numpy dataset with out-of-fold model prediction.

transform(dataset)[source]

Transform dataset to out-of-fold model-based encoding.

Parameters:

dataset (Union[NumpyDataset, PandasDataset]) – Pandas or Numpy dataset of encoded text features.

Return type:

NumpyDataset

Returns:

Numpy dataset with out-of-fold model prediction.