文件名称:LS-SVMLab-v1.7(R2006a-R2009a)

  • 所属分类:
  • matlab例程
  • 资源属性:
  • [Matlab] [源码]
  • 上传时间:
  • 2012-11-26
  • 文件大小:
  • 112kb
  • 下载次数:
  • 0次
  • 提 供 者:
  • 王*
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  • 下载说明:
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matlab中的ls-svm工具包,是最小二乘支持向量机算法,可用于解决非线性的回归问题。-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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下载文件列表

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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