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LS-SVMLab-v1.7(R2006a-R2009a)

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  • Update : 2012-11-26
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Introduction - If you have any usage issues, please Google them yourself
ls-svm tool in the Matlab package, least squares support vector machine algorithm can be used to solve nonlinear regression problems.
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LS-SVMLab v1.7(R2006a-R2009a)\AFEm.m
.............................\bay_errorbar.m
.............................\bay_initlssvm.m
.............................\bay_lssvm.m
.............................\bay_lssvmARD.m
.............................\bay_modoutClass.m
.............................\bay_optimize.m
.............................\bay_rr.m
.............................\changelssvm.m
.............................\cilssvm.m
.............................\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
.............................\crossvalidate.m
.............................\crossvalidatelssvm.m
.............................\csa.m
.............................\democlass.m
.............................\democonfint.m
.............................\demofun.m
.............................\demomodel.m
.............................\demomulticlass.m
.............................\demo_fixedclass.m
.............................\demo_fixedsize.m
.............................\demo_yinyang.m
.............................\denoise_kpca.m
.............................\eign.m
.............................\gcrossvalidate.m
.............................\gcrossvalidatelssvm.m
.............................\gridsearch.m
.............................\initlssvm.m
.............................\kentropy.m
.............................\kernel_matrix.m
.............................\kernel_matrix2.m
.............................\kpca.m
.............................\latentlssvm.m
.............................\leaveoneout.m
.............................\leaveoneoutlssvm.m
.............................\linesearch.m
.............................\linf.m
.............................\lin_kernel.m
.............................\lssvm.m
.............................\lssvmMATLAB.m
.............................\medae.m
.............................\misclass.m
.............................\MLP_kernel.m
.............................\mse.m
.............................\plotlssvm.m
.............................\poly_kernel.m
.............................\postlssvm.m
.............................\predict.m
.............................\predlssvm.m
.............................\preimage_rbf.m
.............................\prelssvm.m
.............................\progress.m
.............................\range.m
.............................\RBF_kernel.m
.............................\rcrossvalidate.m
.............................\rcrossvalidatelssvm.m
.............................\ridgeregress.m
.............................\ripley.mat
.............................\robustlssvm.m
.............................\roc.m
.............................\rsimplex.m
.............................\simann.m
.............................\simlssvm.m
.............................\simplex.m
.............................\smootherlssvm.m
.............................\tbform.m
.............................\trainlssvm.m
.............................\trimmedmse.m
.............................\tunelssvm.m
.............................\weightingscheme.m
.............................\windowize.m
.............................\windowizeNARX.m
LS-SVMLab v1.7(R2006a-R2009a)
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