文件名称:SVM_lusifa
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用于求解支持向量机的二分类问题,对于现实问题进行预测分类-For solving SVM binary classification problem, for reality to predict classification
(系统自动生成,下载前可以参看下载内容)
下载文件列表
SVM_luzhenbo
............\Classification_SVM_SteveGunn.m
............\Classification_SVM_SteveGunn_1.m
............\Classification_stprtool.m
............\Classification_stprtool_1.m
............\LS_SVMlab
............\.........\1.txt
............\.........\2.txt
............\.........\3.txt
............\.........\AFE.m
............\.........\AFE_1.m
............\.........\Classifacation_fourfaults.m
............\.........\Classifacation_fourfaults_1.m
............\.........\Classification_LS_SVMlab.asv
............\.........\Classification_LS_SVMlab.m
............\.........\Classification_LS_SVMlab2.asv
............\.........\Classification_LS_SVMlab_1.m
............\.........\Classification_fourfaults_4000_6000.m
............\.........\Classification_fourfaults_4000_6000_1.m
............\.........\Contents.m
............\.........\Contents_1.m
............\.........\LS-SVMlab Toolbox User's Guide.pdf
............\.........\LS-SVMlab Toolbox User's Guide_1.pdf
............\.........\MLP_kernel.m
............\.........\MLP_kernel_1.m
............\.........\RBF_kernel.m
............\.........\RBF_kernel_1.m
............\.........\bay_errorbar.m
............\.........\bay_errorbar_1.m
............\.........\bay_initlssvm.m
............\.........\bay_initlssvm_1.m
............\.........\bay_lssvm.m
............\.........\bay_lssvmARD.m
............\.........\bay_lssvmARD_1.m
............\.........\bay_lssvm_1.m
............\.........\bay_modoutClass.m
............\.........\bay_modoutClass_1.m
............\.........\bay_optimize.m
............\.........\bay_optimize_1.m
............\.........\bay_rr.m
............\.........\bay_rr_1.m
............\.........\buffer.mc
............\.........\buffer_1.mc
............\.........\changelssvm.m
............\.........\changelssvm_1.m
............\.........\code.m
............\.........\code_1.m
............\.........\code_ECOC.m
............\.........\code_ECOC_1.m
............\.........\code_MOC.m
............\.........\code_MOC_1.m
............\.........\code_OneVsAll.m
............\.........\code_OneVsAll_1.m
............\.........\code_OneVsOne.m
............\.........\code_OneVsOne_1.m
............\.........\codedist_bay.m
............\.........\codedist_bay_1.m
............\.........\codedist_hamming.m
............\.........\codedist_hamming_1.m
............\.........\codedist_loss.m
............\.........\codedist_loss_1.m
............\.........\codelssvm.m
............\.........\codelssvm_1.m
............\.........\crossvalidate.m
............\.........\crossvalidate_1.m
............\.........\deltablssvm.m
............\.........\deltablssvm_1.m
............\.........\demo_fixedclass.m
............\.........\demo_fixedclass_1.m
............\.........\demo_fixedsize.m
............\.........\demo_fixedsize_1.m
............\.........\demo_yinyang.m
............\.........\demo_yinyang_1.m
............\.........\democlass.m
............\.........\democlass_1.m
............\.........\demofun.m
............\.........\demofun_1.m
............\.........\demomodel.m
............\.........\demomodel_1.m
............\.........\denoise_kpca.m
............\.........\denoise_kpca_1.m
............\.........\eign.m
............\.........\eign_1.m
............\.........\gridsearch.m
............\.........\gridsearch_1.m
............\.........\initlssvm.m
............\.........\initlssvm_1.m
............\.........\kentropy.m
............\.........\kentropy_1.m
............\.........\kernel_matrix.m
............\.........\kernel_matrix_1.m
............\.........\kpca.m
............\.........\kpca_1.m
............\.........\latentlssvm.m
............\.........\latentlssvm_1.m
............\.........\leaveoneout.m
............\.........\leaveoneout_1.m
............\.........\leaveoneout_lssvm.m
............\.........\leaveoneout_lssvm_1.m
............\.........\lin_kernel.m