文件名称:gaussianprocess4Clas
介绍说明--下载内容均来自于网络,请自行研究使用
高斯过程是一种非参数化的学习方法,它可以很自然的用于regression,也可以用于classification。本程序用高斯过程实现分类!-Gaussian process is a non - parametric method of learning, it is very natural for regression. can also be used for classification. The procedures used to achieve classification Gaussian process!
(系统自动生成,下载前可以参看下载内容)
下载文件列表
压缩包 : 45666005gaussianprocess4clas.rar 列表 GPC\wuclass.mat GPC\conffig.m GPC\confmat.m GPC\conjgrad.m GPC\consist.m GPC\Contents.m GPC\datread.m GPC\datwrite.m GPC\dem2ddat.m GPC\demard.m GPC\demev1.m GPC\demev2.m GPC\demev3.m GPC\demgauss.m GPC\demglm1.m GPC\demglm2.m GPC\demgmm1.m GPC\demgmm2.m GPC\demgmm3.m GPC\demgmm4.m GPC\demgmm5.m GPC\demgp.m GPC\demgpard.m GPC\demgpot.m GPC\demgtm1.m GPC\demgtm2.m GPC\demhint.m GPC\demhmc1.m GPC\demhmc2.m GPC\demhmc3.m GPC\demkmn1.m GPC\demknn1.m GPC\demmdn1.m GPC\demmet1.m GPC\demmlp1.m GPC\demmlp2.m GPC\demnlab.m GPC\demns1.m GPC\demolgd1.m GPC\demopt1.m GPC\dempot.m GPC\demprgp.m GPC\demprior.m GPC\demrbf1.m GPC\demsom1.m GPC\demtrain.m GPC\dist2.m GPC\eigdec.m GPC\errbayes.m GPC\evidence.m GPC\fevbayes.m GPC\gauss.m GPC\gbayes.m GPC\glm.m GPC\glmderiv.m GPC\glmerr.m GPC\glmevfwd.m GPC\glmfwd.m GPC\glmgrad.m GPC\glmhess.m GPC\glminit.m GPC\glmpak.m GPC\glmtrain.m GPC\glmunpak.m GPC\gmm.m GPC\gmmactiv.m GPC\gmmem.m GPC\gmminit.m GPC\gmmpak.m GPC\gmmpost.m GPC\gmmprob.m GPC\gmmsamp.m GPC\gmmunpak.m GPC\gp.m GPC\gpcovar.m GPC\gpcovarf.m GPC\gpcovarp.m GPC\gperr.m GPC\gpfwd.m GPC\gpgrad.m GPC\gpinit.m GPC\gppak.m GPC\gpunpak.m GPC\gradchek.m GPC\graddesc.m GPC\gsamp.m GPC\gtm.m GPC\gtmem.m GPC\gtmfwd.m GPC\gtminit.m GPC\gtmlmean.m GPC\gtmlmode.m GPC\gtmmag.m GPC\gtmpost.m GPC\gtmprob.m GPC\hbayes.m GPC\hesschek.m GPC\hintmat.m GPC\hinton.m GPC\histp.m GPC\hmc.m GPC\kmeans.m GPC\knn.m GPC\knnfwd.m GPC\LICENSE GPC\linef.m GPC\linemin.m GPC\mdn.m GPC\mdn2gmm.m GPC\mdndist2.m GPC\mdnerr.m GPC\mdnfwd.m GPC\mdngrad.m GPC\mdninit.m GPC\mdnnet.mat GPC\mdnpak.m GPC\mdnpost.m GPC\mdnprob.m GPC\mdnunpak.m GPC\metrop.m GPC\minbrack.m GPC\mlp.m GPC\mlpbkp.m GPC\mlpderiv.m GPC\mlperr.m GPC\mlpevfwd.m GPC\mlpfwd.m GPC\mlpgrad.m GPC\mlphdotv.m GPC\mlphess.m GPC\mlphint.m GPC\mlpinit.m GPC\mlppak.m GPC\mlpprior.m GPC\mlptrain.m GPC\mlpunpak.m GPC\netderiv.m GPC\neterr.m GPC\netevfwd.m GPC\netgrad.m GPC\nethess.m GPC\netinit.m GPC\netlogo.mat GPC\netopt.m GPC\netpak.m GPC\netunpak.m GPC\oilTrn.dat GPC\oilTst.dat GPC\olgd.m GPC\pca.m GPC\plotmat.m GPC\ppca.m GPC\quasinew.m GPC\rbf.m GPC\rbfbkp.m GPC\rbfderiv.m GPC\rbferr.m GPC\rbfevfwd.m GPC\rbffwd.m GPC\rbfgrad.m GPC\rbfhess.m GPC\rbfjacob.m GPC\rbfpak.m GPC\rbfprior.m GPC\rbfsetbf.m GPC\rbfsetfw.m GPC\rbftrain.m GPC\rbfunpak.m GPC\rosegrad.m GPC\rosen.m GPC\scg.m GPC\som.m GPC\somfwd.m GPC\sompak.m GPC\somtrain.m GPC\somunpak.m GPC\xor.dat GPC\GP_classifydemo.m GPC\GP_classify.m GPC