RSSL (version 0.9.3)

LinearSVM: Linear SVM Classifier

Description

Implementation of the Linear Support Vector Classifier. Can be solved in the Dual formulation, which is equivalent to SVM or the Primal formulation.

Usage

LinearSVM(X, y, C = 1, method = "Dual", scale = TRUE, eps = 1e-09,
  reltol = 1e-13, maxit = 100)

Arguments

X

matrix; Design matrix for labeled data

y

factor or integer vector; Label vector

C

Cost variable

method

Estimation procedure c("Dual","Primal","BGD")

scale

Whether a z-transform should be applied (default: TRUE)

eps

Small value to ensure positive definiteness of the matrix in QP formulation

reltol

relative tolerance using during BFGS optimization

maxit

Maximum number of iterations for BFGS optimization

Value

S4 object of type LinearSVM

See Also

Other RSSL classifiers: EMLeastSquaresClassifier, EMLinearDiscriminantClassifier, GRFClassifier, ICLeastSquaresClassifier, ICLinearDiscriminantClassifier, KernelLeastSquaresClassifier, LaplacianKernelLeastSquaresClassifier(), LaplacianSVM, LeastSquaresClassifier, LinearDiscriminantClassifier, LinearTSVM(), LogisticLossClassifier, LogisticRegression, MCLinearDiscriminantClassifier, MCNearestMeanClassifier, MCPLDA, MajorityClassClassifier, NearestMeanClassifier, QuadraticDiscriminantClassifier, S4VM, SVM, SelfLearning, TSVM, USMLeastSquaresClassifier, WellSVM, svmlin()