文件名称:SVM

  • 所属分类:
  • 其他小程序
  • 资源属性:
  • [Matlab] [源码]
  • 上传时间:
  • 2012-11-26
  • 文件大小:
  • 365kb
  • 下载次数:
  • 0次
  • 提 供 者:
  • M***
  • 相关连接:
  • 下载说明:
  • 别用迅雷下载,失败请重下,重下不扣分!

介绍说明--下载内容均来自于网络,请自行研究使用

有基于 matlav的svm软件工具,感觉挺好用的。里面有很多实例,稍加修改就可以使用。例如三分类问题:

1、输入三类数据xapp yapp

2、选择多类分类方法(一对多或一对一或m-svm)

3、设置参数

4、调用训练函数得到向量机参数

5、输入测试数据,得到预期结果。

-There is matlav based on the SVM-based software tools, I feel pretty useless. Inside there is a lot of examples you can use a little modification. Categories such as three questions: 1, three types of data input xapp yapp 2, selection multiclass classification methods (one-to-many or one-on-one or m-svm) 3, set the parameters of 4, call the training function to be vector machine parameters 5, enter test data, the expected results.
(系统自动生成,下载前可以参看下载内容)

下载文件列表

SVM

...\AdaptScalSVM

...\............\costlbfixed.m

...\............\costlfixed.m

...\............\costwbfixed.m

...\............\costwfixed.m

...\............\ExampledemoAdaptScal.m

...\............\ExampleFeatSelAdaptScal.m

...\............\gradlbfixed.m

...\............\gradlfixed.m

...\............\gradwbfixed.m

...\............\gradwfixed.m

...\............\LagrangeUpdate.m

...\............\SigmaUpdate.m

...\............\svmfit.asv

...\............\svmfit.m

...\............\svmfitconj.m

...\contents.m

...\cout.m

...\dataset1.mat

...\dataset2.mat

...\dataset3.mat

...\datasets.m

...\featselreg

...\..........\exfeatselreg1.m

...\..........\FeatSelregalpha.m

...\..........\FeatSelregalphaGD.m

...\..........\FeatSelregalphaGDrandom.m

...\..........\FeatSelreglinearL1.m

...\..........\FeatSelregmargin.m

...\..........\FeatSelregmarginGD.m

...\..........\FeatSelregmarginGDrandom.m

...\..........\FeatSelregr2w2.m

...\..........\FeatSelregr2w2GD.m

...\..........\FeatSelregr2w2GDrandom.m

...\..........\FeatSelregspanbound.m

...\..........\FeatSelregspanboundGD.m

...\..........\FeatSelregspanboundGDrandom.m

...\..........\r2alpharegL2.m

...\..........\spanestimateregL2.m

...\FeatureSelection

...\................\featselcorrcoeff.m

...\................\featselkernelderivative.m

...\................\FeatSelmargdif.m

...\................\FeatSelmargdif1v1.m

...\................\FeatSelmargin.m

...\................\FeatSelr2w2.m

...\................\FeatSelr2w2diff.m

...\fileaccess.m

...\functioneval.m

...\gda.m

...\givrot.m

...\kbp

...\...\BuildTrapScale.m

...\...\calcdistance.m

...\...\CalcTrapScale.m

...\...\exlar.m

...\...\exlar1.m

...\...\exlarrealdata.m

...\...\exlarsignalclassif.m

...\...\exmultikernellarclass.m

...\...\HingeLAR.m

...\...\HingeLAR2.m

...\...\LAR.m

...\...\LARval.m

...\...\multiplekernel.m

...\...\normalizekernelLAR.m

...\...\plot2Ddec.m

...\...\pyrim.mat

...\...\testHingeLAR.m

...\kernelpca.m

...\kernelpcaproj.m

...\kernelset.m

...\libsvminterface

...\...............\mexSVMClass.dll

...\...............\mexSVMClass.mexglx

...\...............\mexSVMTrain.dll

...\...............\mexSVMTrain.mexglx

...\...............\svmclasslib.m

...\...............\svmvallib.m

...\license.txt

...\LPsvmclass.m

...\LPsvmreg.m

...\monqp.m

...\monqpCinfty.m

...\normalizekernel.m

...\phispan.m

...\r2smallestsphere.m

...\regpath

...\.......\exregpathoneclasssvm.asv

...\.......\exregpathoneclasssvm.m

...\.......\regpathsvmoneclass.m

...\.......\TransformPathFromNu.m

...\regsolve.m

...\rncalc.m

...\rnval.m

...\spanestimate.m

...\svmclass.m

...\svmclassL2.m

...\svmclassL2LS.m

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