gemseo / mlearning / transform / power

power module

A power transform, either Yeo-Johnson or Box-Cox.

Dependence

This transformation algorithm relies on the PowerTransformer class of scikit-learn.

class gemseo.mlearning.transform.power.power.Power(name=None, standardize=True)[source]

Bases: Transformer

A power transformation.

Parameters:

  • name (str) – A name for this transformer. If None, use the class name.

  • standardize (bool) –

    Whether to apply zero-mean, unit-variance normalization to the transformed output.

    By default it is set to True.

compute_jacobian(data)

Compute Jacobian of transformer.transform().

Parameters:

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

Returns:

The Jacobian matrix.

Return type:

NoReturn

compute_jacobian_inverse(data)

Compute Jacobian of the transformer.inverse_transform().

Parameters:

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

Returns:

The Jacobian matrix.

Return type:

NoReturn

duplicate()

Duplicate the current object.

Returns:

A deepcopy of the current instance.

Return type:

Transformer

fit(data, *args)

Fit the transformer to the data.

Parameters:
Return type:

NoReturn

fit_transform(data, *args)

Fit the transformer to the data and transform the data.

Parameters:
Returns:

The transformed data.

Return type:

ndarray

inverse_transform(data)[source]

Perform an inverse transform on the data.

Parameters:

data (ndarray) – The data to be inverse transformed.

Returns:

The inverse transformed data.

Return type:

ndarray

transform(data)[source]

Transform the data.

Parameters:

data (ndarray) – The data to be transformed.

Returns:

The transformed data.

Return type:

ndarray

CROSSED = False
lambdas_: ndarray

The parameters of the power transformation for the selected features.

name: str

The name of the transformer.

parameters: str

The parameters of the transformer.