pls module¶
The Partial Least Square (PLS) regression to reduce the dimension of a variable.
The PLS
class wraps the PCA from Scikit-learn.
Dependence¶
This dimension reduction algorithm relies on the PLSRegression class of the scikit-learn library.
- class gemseo.mlearning.transformers.dimension_reduction.pls.PLS(name='', n_components=None, **parameters)[source]
Bases:
DimensionReduction
Partial Least Square regression.
- Parameters:
name (str) –
A name for this transformer.
By default it is set to “”.
n_components (int | None) – The number of components of the latent space. If
None
, use the maximum number allowed by the technique, typicallymin(n_samples, n_features)
.**parameters (float | int | bool) – The optional parameters for sklearn PCA constructor.
- inverse_transform(data, *args, **kwargs)
Force a NumPy array to be 2D and evaluate the function
f
with it.
- transform(data, *args, **kwargs)
Force a NumPy array to be 2D and evaluate the function
f
with it.
- name: str
The name of the transformer.