Description: 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.
- [montecarlo] - this document, including the Monte Carlo
- [svm_v0.51beta.tar] - SVM source of small samples for analysis
- [KNN] - matlab source KNN classification
- [svm] - SVM-based text classification is the cor
- [Iris] - Pattern recognition, classification of i
- [MATLA+svm] - SVM prepared using MATLAB source code, y
- [Regression_SVM_SteveGunn] - SVM regression algorithm. Want to use wh
- [mill] - Contains a lot of classification algorit
- [ga-PID] - The use of genetic algorithm to optimize
- [SVMclassifier] - SVM classifier, multi-dimensional sampli
File list (Check if you may need any files):
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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