The SVM can be seen as a method of training polynomial, radial basis function, or multilayer perception classifiers, in which the weights of the network are found by solving a quadratic programming (QP) problem with linear inequality and equality constraints.

LS_SVMlab\AFE.m
.........\bay_errorbar.m
.........\bay_initlssvm.m
.........\bay_lssvm.m
.........\bay_lssvmARD.m
.........\bay_modoutClass.m
.........\bay_optimize.m
.........\bay_rr.m
.........\buffer.mc
.........\changelssvm.m
.........\code.asv
.........\code.m
.........\codedist_bay.m
.........\codedist_hamming.m
.........\codedist_loss.m
.........\codelssvm.m
.........\code_ECOC.m
.........\code_MOC.m
.........\code_OneVsAll.m
.........\code_OneVsOne.m
.........\Contents.m
.........\crossvalidate.m
.........\deltablssvm.m
.........\democlass.m
.........\demofun.m
.........\demomodel.m
.........\demo_fixedclass.m
.........\demo_fixedsize.m
.........\demo_yinyang.m
.........\denoise_kpca.m
.........\eign.m
.........\gridsearch.m
.........\initlssvm.m
.........\kentropy.m
.........\kernel_matrix.m
.........\kpca.m
.........\latentlssvm.m
.........\leaveoneout.m
.........\leaveoneout_lssvm.m
.........\linesearch.m
.........\linf.m
.........\lin_kernel.m
.........\LS-SVMlab Toolbox User's Guide.pdf
.........\lssvm.dll
.........\lssvm1024.dll
.........\lssvm256.dll
.........\lssvm64.dll
.........\lssvmFILE.m
.........\lssvmMATLAB.m
.........\LS_SVM2.asv
.........\medae.m
.........\misclass.m
.........\MLP_kernel.m
.........\mse1.m
.........\phitures.dll
.........\plotlssvm.m
.........\poly_kernel.m
.........\postlssvm.m
.........\predict.m
.........\prelssvm.m
.........\RBF_kernel.m
.........\rcrossvalidate.m
.........\ridgeregress.m
.........\robustlssvm.m
.........\roc.m
.........\simclssvm.dll
.........\simclssvm1024.dll
.........\simclssvm256.dll
.........\simclssvm64.dll
.........\simFILE.m
.........\simlssvm.m
.........\sparselssvm.m
.........\trainlssvm.m
.........\trimmedmse.m
.........\tunelssvm.m
.........\validate.m
.........\windowize.m
.........\windowizeNARX.m
LS_SVMlab

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