Linear SVM Classifier
Implementation of the Linear Support Vector Classifier. Can be solved in the Dual formulation, which is equivalent to SVM or the Primal formulation.
LinearSVM(X, y, C = 1, method = "Dual", scale = TRUE, eps = 1e-09, reltol = 1e-13, maxit = 100)
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 |
S4 object of type LinearSVM
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()
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