gemseo / mlearning / transform / power

yeo_johnson module

A Yeo-Johnson power transformation.

Transform \(x\) as:

\[\begin{split}y = & ((x + 1)^\lambda - 1) / \lambda, \text{ for } x \geq 0, \lambda \neq 0 \\\\ & \log(x + 1), \text{ for }x \geq 0, \lambda = 0 \\\\ & -\frac{(1-x)^{2 - \lambda} - 1}{2-\lambda}, \text{for} x < 0, \lambda \neq 2\\\\ & -log(1-x), \text{ for } x < 0, \lambda = 2\end{split}\]

Dependence

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

class gemseo.mlearning.transform.power.yeo_johnson.YeoJohnson(name=None, standardize=True)

Bases: Power

A Yeo-Johnson 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:

• data (ndarray) – The data to be fitted.

• args (Union[float, int, str]) –

Return type:

NoReturn

fit_transform(data, *args)

Fit the transformer to the data and transform the data.

Parameters:

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

• args (Union[float, int, str]) –

Returns:

The transformed data.

Return type:

ndarray

inverse_transform(data)

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)

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.