Support vector machine (SVM) commercial software package in matlab, accompanied by Chinese and English manual, can be on the basis of the algorithm does not understand, using simple commands to complete the support vector machine (SVM) classification and regression modeling

tutorialv1_8.pdf
LSSVMlabv1_8_R2009b_R2011a\AFEm.m
..........................\bay_errorbar.m
..........................\bay_initlssvm.m
..........................\bay_lssvm.m
..........................\bay_lssvmARD.m
..........................\bay_modoutClass.m
..........................\bay_optimize.m
..........................\bay_rr.m
..........................\bitreverse32.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
..........................\latticeseq_b2.m
..........................\leaveoneout.m
..........................\leaveoneoutlssvm.m
..........................\linesearch.m
..........................\linf.m
..........................\lin_kernel.m
..........................\lssvm.m
..........................\lssvmMATLAB.m
..........................\mae.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
..........................\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-SVM相关教程.doc
LSSVMlabv1_8_R2009b_R2011a

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