先将LSSVMlabv右键——添加到路径——选定的文件夹和子文件夹
使用WOA_LSSVM程序直接运行即可。
北方苍鹰算法(NGO)优化最小二乘支持向量机回归预测，NGO-LSSVM回归预测，多变量输入模型 评价指标包括:R2、MAE
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2023-09-18
17:29:41
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8.18 NGO-LSSVM - 2.zip （88个子文件） 
initialization.m 459B
LSSVMlabv roc.m 7KB bay_rr.m 4KB windowizeNARX.m 2KB trainlssvm.m 9KB demo_fixedsize.m 3KB code_ECOC.m 5KB weightingscheme.m 928B codelssvm.m 4KB code_MOC.m 548B kernel_matrix2.m 795B simplex.m 10KB kpca.m 6KB lssvmMATLAB.m 2KB lssvm.m 2KB csa.m 3KB predict.m 3KB bay_lssvmARD.m 8KB demofun.m 4KB initlssvm.m 3KB rsimplex.m 10KB predlssvm.m 5KB lin_kernel.m 529B eign.m 4KB leaveoneoutlssvm.m 2KB ridgeregress.m 1KB preimage_rbf.m 4KB range.m 173B progress.m 1KB gcrossvalidate.m 3KB leaveoneout.m 4KB codedist_loss.m 2KB smootherlssvm.m 1KB postlssvm.m 5KB rcrossvalidatelssvm.m 4KB mae.m 281B demomulticlass.m 2KB demo_yinyang.m 3KB rcrossvalidate.m 6KB gridsearch.m 7KB codedist_bay.m 2KB windowize.m 2KB code_OneVsAll.m 361B prelssvm.m 6KB kernel_matrix.m 3KB crossvalidatelssvm.m 4KB democonfint.m 2KB gcrossvalidatelssvm.m 2KB tunelssvm.m 23KB kentropy.m 2KB bay_optimize.m 6KB crossvalidate.m 6KB democlass.m 3KB cilssvm.m 5KB trimmedmse.m 2KB changelssvm.m 5KB linf.m 310B latticeseq_b2.m 6KB robustlssvm.m 2KB misclass.m 684B bitreverse32.m 1KB MLP_kernel.m 603B demo_fixedclass.m 2KB bay_modoutClass.m 9KB code_OneVsOne.m 576B simann.m 5KB poly_kernel.m 623B linesearch.m 4KB bay_initlssvm.m 2KB bay_errorbar.m 6KB plotlssvm.m 10KB demomodel.m 5KB RBF_kernel.m 1KB latentlssvm.m 2KB tbform.m 3KB bay_lssvm.m 10KB codedist_hamming.m 753B denoise_kpca.m 4KB medae.m 302B simlssvm.m 6KB AFEm.m 3KB code.m 4KB
使用说明.png 30KB main.m 1KB fitnessfunclssvm.m 617B
使用说明.txt 127B NGO.m 2KB
data.xlsx 36KB资源评论
