tabensemb.data.datamodule.DataModule.pca#

method

DataModule.pca(feature_names: List[str] | None = None, feature_idx: List[int] | None = None, indices: ndarray | None = None, **kwargs) → PCA[source]#

Perform sklearn.decomposition.PCA

Parameters:

feature_names: A list of names of continuous features.
feature_idx: Indices in cont_feature_names of continuous features.
indices: Indices of investigated data points. If is None, train_indices is used.
**kwargs: Arguments of sklearn.decomposition.PCA.

Returns:

sklearn.decomposition.PCA: A sklearn.decomposition.PCA instance.