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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/SVM.R
\name{SVM}
\alias{SVM}
\title{SVM Classifier}
\usage{
SVM(X, y, C = 1, kernel = NULL, scale = TRUE, intercept = FALSE,
x_center = TRUE, eps = 1e-09)
}
\arguments{
\item{X}{matrix; Design matrix for labeled data}
\item{y}{factor or integer vector; Label vector}
\item{C}{numeric; Cost variable}
\item{kernel}{kernlab::kernel to use}
\item{scale}{logical; Should the features be normalized? (default: FALSE)}
\item{intercept}{logical; Whether an intercept should be included}
\item{x_center}{logical; Should the features be centered?}
\item{eps}{numeric; Small value to ensure positive definiteness of the matrix in the QP formulation}
}
\value{
S4 object of type SVM
}
\description{
Support Vector Machine implementation using the \code{quadprog} solver.
}
\details{
This implementation will typically be slower and use more memory than the svmlib implementation in the e1071 package. It is, however, useful for comparisons with the \code{\link{TSVM}} implementation.
}
\seealso{
Other RSSL classifiers:
\code{\link{EMLeastSquaresClassifier}},
\code{\link{EMLinearDiscriminantClassifier}},
\code{\link{GRFClassifier}},
\code{\link{ICLeastSquaresClassifier}},
\code{\link{ICLinearDiscriminantClassifier}},
\code{\link{KernelLeastSquaresClassifier}},
\code{\link{LaplacianKernelLeastSquaresClassifier}()},
\code{\link{LaplacianSVM}},
\code{\link{LeastSquaresClassifier}},
\code{\link{LinearDiscriminantClassifier}},
\code{\link{LinearSVM}},
\code{\link{LinearTSVM}()},
\code{\link{LogisticLossClassifier}},
\code{\link{LogisticRegression}},
\code{\link{MCLinearDiscriminantClassifier}},
\code{\link{MCNearestMeanClassifier}},
\code{\link{MCPLDA}},
\code{\link{MajorityClassClassifier}},
\code{\link{NearestMeanClassifier}},
\code{\link{QuadraticDiscriminantClassifier}},
\code{\link{S4VM}},
\code{\link{SelfLearning}},
\code{\link{TSVM}},
\code{\link{USMLeastSquaresClassifier}},
\code{\link{WellSVM}},
\code{\link{svmlin}()}
}
\concept{RSSL classifiers}