This is documentation for an old release of Scikit-learn (version 1.1). Try the latest stable release (version 1.6) or development (unstable) versions.

Support Vector Machines

Examples concerning the sklearn.svm module.

Non-linear SVM

Non-linear SVM

One-class SVM with non-linear kernel (RBF)

One-class SVM with non-linear kernel (RBF)

Plot different SVM classifiers in the iris dataset

Plot different SVM classifiers in the iris dataset

Plot the support vectors in LinearSVC

Plot the support vectors in LinearSVC

RBF SVM parameters

RBF SVM parameters

SVM Margins Example

SVM Margins Example

SVM Tie Breaking Example

SVM Tie Breaking Example

SVM with custom kernel

SVM with custom kernel

SVM-Anova: SVM with univariate feature selection

SVM-Anova: SVM with univariate feature selection

SVM-Kernels

SVM-Kernels

SVM: Maximum margin separating hyperplane

SVM: Maximum margin separating hyperplane

SVM: Separating hyperplane for unbalanced classes

SVM: Separating hyperplane for unbalanced classes

SVM: Weighted samples

SVM: Weighted samples

Scaling the regularization parameter for SVCs

Scaling the regularization parameter for SVCs

Support Vector Regression (SVR) using linear and non-linear kernels

Support Vector Regression (SVR) using linear and non-linear kernels