gemseo.mlearning.transformers.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 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 at least 2D and evaluate the function f.

f expects a 2D array shaped as (n_points, input_dimension) and returns a nD arrays shaped as (..., n_points, output_dimension) or (..., n_points, output_dimension, input_dimension).

If the original data is a 1D array shaped as (input_dimension,), then this wrapper returns a (n-1)D array shaped as (..., output_dimension) or (..., output_dimension, intput_dimension).

Parameters:

  • data (ndarray) -- A 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 at least 2D and evaluate the function f.

f expects a 2D array shaped as (n_points, input_dimension) and returns a nD arrays shaped as (..., n_points, output_dimension) or (..., n_points, output_dimension, input_dimension).

If the original data is a 1D array shaped as (input_dimension,), then this wrapper returns a (n-1)D array shaped as (..., output_dimension) or (..., output_dimension, intput_dimension).

Parameters:

  • data (ndarray) -- A 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.