PCATransformer

class lightautoml.transformers.decomposition.PCATransformer(subs=None, random_state=42, n_components=500)[source]

Bases: lightautoml.transformers.base.LAMLTransformer

PCA.

property features

Features list.

Return type

List[str]

__init__(subs=None, random_state=42, n_components=500)[source]
Parameters

  • subs (Optional[int]) – Subsample to fit algorithm. If None - full data.

  • random_state (int) – Random state to take subsample.

  • n_components (int) – Number of PCA components

fit(dataset)[source]

Fit algorithm on dataset.

Parameters

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

transform(dataset)[source]

Transform input dataset to PCA representation.

Parameters

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

Return type

NumpyDataset

Returns

Numpy dataset with text embeddings.