gemseo / mlearning / transform / dimension_reduction

pca module

Principal component dimension reduction algorithm

The PCA class wraps the PCA from Scikit-learn.

Dependence

This dimension reduction algorithm relies on the PCA class of the scikit-learn library.

class gemseo.mlearning.transform.dimension_reduction.pca.PCA(name='PCA', n_components=5, **parameters)[source]

Bases: gemseo.mlearning.transform.dimension_reduction.dimension_reduction.DimensionReduction

Principal component dimension reduction algorithm.

Constructor.

Parameters

  • name (str) – transformer name. Default: ‘PCA’.

  • n_components (int) – number of components. Default: 5.

  • parameters – Optional parameters for sklearn PCA constructor.

property components

Components

compute_jacobian(data)[source]

Compute Jacobian of the pca transform.

Parameters

data (ndarray) – data where the Jacobian is to be computed.

Returns

Jacobian matrix.

Return type

ndarray

compute_jacobian_inverse(data)[source]

Compute Jacobian of the pca inverse_transform.

Parameters

data (ndarray) – data where the Jacobian is to be computed.

Returns

Jacobian matrix.

Return type

ndarray

fit(data)[source]

Fit transformer to data.

Parameters

data (ndarray) – data to be fitted.

inverse_transform(data)[source]

Perform an inverse transform on the data.

Parameters

data (ndarray) – data to be inverse transformed.

Returns

inverse transformed data.

Return type

ndarray

transform(data)[source]

Transform data.

Parameters

data (ndarray) – data to be transformed.

Returns

transformed data.

Return type

ndarray