Support Vector Machines

Examples concerning the sklearn.svm module.

Non-linear SVM

Non-linear SVM

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

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 different SVM classifiers in the iris dataset
Plot the support vectors in LinearSVC

Plot the support vectors in LinearSVC

Plot the support vectors in LinearSVC
RBF SVM parameters

RBF SVM parameters

RBF SVM parameters
SVM Margins Example

SVM Margins Example

SVM Margins Example
SVM Tie Breaking Example

SVM Tie Breaking Example

SVM Tie Breaking Example
SVM with custom kernel

SVM with custom kernel

SVM with custom kernel
SVM-Anova: SVM with univariate feature selection

SVM-Anova: SVM with univariate feature selection

SVM-Anova: SVM with univariate feature selection
SVM-Kernels

SVM-Kernels

SVM-Kernels
SVM: Maximum margin separating hyperplane

SVM: Maximum margin separating hyperplane

SVM: Maximum margin separating hyperplane
SVM: Separating hyperplane for unbalanced classes

SVM: Separating hyperplane for unbalanced classes

SVM: Separating hyperplane for unbalanced classes
SVM: Weighted samples

SVM: Weighted samples

SVM: Weighted samples
Scaling the regularization parameter for SVCs

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

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