Generalized Linear Models#
Examples concerning the sklearn.linear_model
module.
![](../../_images/sphx_glr_plot_elastic_net_precomputed_gram_matrix_with_weighted_samples_thumb.png)
Fitting an Elastic Net with a precomputed Gram Matrix and Weighted Samples
Fitting an Elastic Net with a precomputed Gram Matrix and Weighted Samples
![](../../_images/sphx_glr_plot_huber_vs_ridge_thumb.png)
HuberRegressor vs Ridge on dataset with strong outliers
HuberRegressor vs Ridge on dataset with strong outliers
![](../../_images/sphx_glr_plot_sparse_logistic_regression_mnist_thumb.png)
MNIST classification using multinomial logistic + L1
MNIST classification using multinomial logistic + L1
![](../../_images/sphx_glr_plot_sparse_logistic_regression_20newsgroups_thumb.png)
Multiclass sparse logistic regression on 20newgroups
Multiclass sparse logistic regression on 20newgroups
![](../../_images/sphx_glr_plot_sgdocsvm_vs_ocsvm_thumb.png)
One-Class SVM versus One-Class SVM using Stochastic Gradient Descent
One-Class SVM versus One-Class SVM using Stochastic Gradient Descent
![](../../_images/sphx_glr_plot_ols_ridge_variance_thumb.png)
Ordinary Least Squares and Ridge Regression Variance
Ordinary Least Squares and Ridge Regression Variance
![](../../_images/sphx_glr_plot_ridge_path_thumb.png)
Plot Ridge coefficients as a function of the regularization
Plot Ridge coefficients as a function of the regularization
![](../../_images/sphx_glr_plot_logistic_multinomial_thumb.png)
Plot multinomial and One-vs-Rest Logistic Regression
Plot multinomial and One-vs-Rest Logistic Regression
![](../../_images/sphx_glr_plot_ridge_coeffs_thumb.png)
Ridge coefficients as a function of the L2 Regularization
Ridge coefficients as a function of the L2 Regularization