gemseo.mlearning.linear_model_fitting.ridge_cv module

Scikit-learn ridge algorithm with built-in cross-validation.

class RidgeCV(settings=None)

Bases: BaseSKLearnLinearModelFitter[RidgeCV, RidgeCV_Settings]

Scikit-learn ridge algorithm with built-in cross-validation.

Given the linear model fitting problem presented in this page, this algorithm solves a penalized least squares problem of the form:

\[\min_w \|Xw-y\|_2^2 + \alpha \|w\|_2^2\]

where \(\|w\|_2\) is the \(\ell_2\)-norm of the coefficients \(w\), \(\|Xw-y\|_2\) is the \(\ell_2\)-norm of the residual \(Xw-y\) and \(\alpha>0\) is estimated by cross-validation.

Initialize self. See help(type(self)) for accurate signature.

Parameters:

settings (SettingsType | None) -- The settings of the linear model fitting algorithm. If None, use a default instance of Settings.

Settings

alias of RidgeCV_Settings