Title:
SuportVectorMachine_Library
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Description: This toolbox was designed as a teaching aid, which matlab is
particularly good for since source code is relatively legible and
simple to modify. However, it is still reasonably fast if used
with the supplied optimiser. However, if you really want to speed
things up you should consider compiling the matrix composition
routine for H into a mex function. Then again if you really want
to speed things up you probably shouldn t be using matlab
anyway... Get hold of a dedicated C program once you understand
the algorithm.
To Search:
File list (Check if you may need any files):
SuportVectorMachine_Library\svm\binomial.m
...........................\...\centrefig.m
...........................\...\cmap.mat
...........................\...\Contents.m
...........................\...\Examples\Classification\iris1v23.mat
...........................\...\........\..............\iris2v13.mat
...........................\...\........\..............\iris3v12.mat
...........................\...\........\..............\linsep.mat
...........................\...\........\..............\nlinsep.mat
...........................\...\........\Regression\example.mat
...........................\...\........\..........\sinc.mat
...........................\...\........\..........\titanium.mat
...........................\...\newsvm.zip
...........................\...\nobias.m
...........................\...\Optimiser\Makefile
...........................\...\.........\pr_loqo.c
...........................\...\.........\pr_loqo.h
...........................\...\.........\qp.c
...........................\...\.........\qp.dll
...........................\...\qp.dll
...........................\...\README
...........................\...\softmargin.m
...........................\...\svc.m
...........................\...\svcerror.m
...........................\...\svcinfo.m
...........................\...\svcoutput.m
...........................\...\svcplot.m
...........................\...\svdatanorm.m
...........................\...\svkernel.m
...........................\...\svr.m
...........................\...\svrerror.m
...........................\...\svroutput.m
...........................\...\svrplot.m
...........................\...\svtol.m
...........................\...\uiclass.m
...........................\...\uiclass.mat
...........................\...\uiregress.m
...........................\...\uiregress.mat
...........................\...\Examples\Classification
...........................\...\........\Regression
...........................\...\Examples
...........................\...\Optimiser
...........................\svm
SuportVectorMachine_Library
