gemseo / mlearning / transformers / power

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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.transformers.power.power.Power(name='', standardize=True)[source]

Bases: BaseTransformer

A power transformation.

Parameters:

  • name (str) –

    A name for this transformer. If None, use the class name.

    By default it is set to “”.

  • standardize (bool) –

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

    By default it is set to True.

inverse_transform(data, *args, **kwargs)

Force a NumPy array to be 2D and evaluate the function f with it.

Parameters:

  • data (ndarray) – A 1D or 2D NumPy array.

  • *args (Any) – The positional arguments.

  • **kwargs (Any) – The optional arguments.

Returns:

Any kind of output; if a NumPy array, its dimension is made consistent with the shape of data.

Return type:

Any

transform(data, *args, **kwargs)

Force a NumPy array to be 2D and evaluate the function f with it.

Parameters:

  • data (ndarray) – A 1D or 2D NumPy array.

  • *args (Any) – The positional arguments.

  • **kwargs (Any) – The optional arguments.

Returns:

Any kind of output; if a NumPy array, its dimension is made consistent with the shape of data.

Return type:

Any

lambdas_: RealArray

The parameters of the power transformation for the selected features.

name: str

The name of the transformer.