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  • Update : 2008-10-13
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  • Author :che****
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Introduction - If you have any usage issues, please Google them yourself
MATLAB-SVM algorithm, Matlab Support Vector Machine Toolbox, This toolbox was designed as a teaching aid, which matlab isparticularly good for since source code is relatively legible andsimple to modify. However, it is still reasonably fast if usedwith the supplied optimiser. However , if you really want to speedthings up you should consider compiling the matrix compositionroutine for H into a mex function. Then again if you really wantto speed things up you probably shouldn t be using matlabanyway ... Get hold of a dedicated C program once you understandthe algorithm.
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Packet : 115157686svm_new.rar filelist
svm
svm\binomial.m
svm\centrefig.m
svm\cmap.mat
svm\Contents.m
svm\Examples
svm\Examples\Classification
svm\Examples\Classification\iris1v23.mat
svm\Examples\Classification\iris2v13.mat
svm\Examples\Classification\iris3v12.mat
svm\Examples\Classification\linsep.mat
svm\Examples\Classification\nlinsep.mat
svm\Examples\Regression
svm\Examples\Regression\example.mat
svm\Examples\Regression\sinc.mat
svm\Examples\Regression\titanium.mat
svm\hs_err_pid2808.log
svm\knn.asv
svm\knn.m
svm\newsvm.zip
svm\nobias.m
svm\Optimiser
svm\Optimiser\Makefile
svm\Optimiser\pr_loqo.c
svm\Optimiser\pr_loqo.h
svm\Optimiser\qp.c
svm\Optimiser\qp.dll
svm\qp.dll
svm\README
svm\softmargin.m
svm\svc.m
svm\svcerror.m
svm\svcinfo.m
svm\svcoutput.m
svm\svcplot.m
svm\svdatanorm.m
svm\svkernel.m
svm\svr.m
svm\svrerror.m
svm\svroutput.m
svm\svrplot.m
svm\svtol.m
svm\uiclass.m
svm\uiclass.mat
svm\uiregress.m
svm\uiregress.mat
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