boxcox module¶

A Box-Cox power transformation.

Transform a variable \(x\) as:

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

Dependence¶

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

class gemseo.mlearning.transformers.power.boxcox.BoxCox(name='', standardize=True)[source]

A Box-Cox 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.

lambdas_: RealArray: The parameters of the power transformation for the selected features.