This is documentation for an old release of Scikit-learn (version 1.3). Try the latest stable release (version 1.6) or development (unstable) versions.
Generalized Linear Models¶
Examples concerning the sklearn.linear_model
module.

Fitting an Elastic Net with a precomputed Gram Matrix and Weighted Samples

HuberRegressor vs Ridge on dataset with strong outliers

MNIST classification using multinomial logistic + L1

Multiclass sparse logistic regression on 20newgroups

One-Class SVM versus One-Class SVM using Stochastic Gradient Descent

Ordinary Least Squares and Ridge Regression Variance

Plot Ridge coefficients as a function of the regularization

Plot multinomial and One-vs-Rest Logistic Regression

Ridge coefficients as a function of the L2 Regularization