function?[featureseigveceigvals]?=?AFE（Xskernel?kernel_parsXtypenbeigveceigvals）
%?Automatic?Feature?Extraction?by?Nystr鰉?method
%
%
%?>>?features?=?AFE（X?kernel?sig2?Xt）
%
%?Description
%?Using?the?Nystr鰉?approximation?method?the?mapping?of?data?to
%?the?feature?space?can?be?evaluated?explicitly.?This?gives?the
%?features?that?one?can?use?for?a?linear?regression?or
%?classification.?The?decomposition?of?the?mapping?to?the?feature
%?space?relies?on?the?eigenvalue?decomposition?of?the?kernel
%?matrix.?The?Matlab?（‘eigs‘）?or?Nystr鰉‘s?（‘eign‘）?approximation
%?using?the?nb?most?important?eigenvectors/eigenvalues?can?be
%?used.?The?eigenvalue?decomposition?is?not?re-calculated?if?it?is
%?passed?as?an?extra?argument.?This?routine?internally?calls?a?cmex?file.
%
%?Full?syntax
%?
%?>>?[features?U?lam]?=?AFE（X?kernel?sig2?Xt）?
%?>>?[features?U?lam]?=?AFE（X?kernel?sig2?Xt?type）?
%?>>?[features?U?lam]?=?AFE（X?kernel?sig2?Xt?type?nb）?
%?>>?features??????????=?AFE（X?kernel?sig2?Xt?[][]?U?lam）
%?
%?Outputs????
%???features?:?Nt?x?nb?matrix?with?extracted?features
%???U（*）?????:?N?x?nb?matrix?with?eigenvectors
%???lam（*）???:?nb?x?1?vector?with?eigenvalues
%?Inputs????
%???X??????:?N?x?d?matrix?with?input?data
%???kernel?:?Name?of?the?used?kernel?（e.g.?‘RBF_kernel‘）
%???sig2???:?parameter?of?the?used?kernel
%???Xt?????:?Data?from?which?the?features?are?extracted
%???type（*）:?‘eig‘（*）?‘eigs‘?or?‘eign‘
%???nb（*）??:?Number?of?eigenvalues/eigenvectors?used?in?the?eigenvalue?decomposition?approximation
%???U（*）???:?N?x?nb?matrix?with?eigenvectors
%???lam（*）?:?nb?x?1?vector?with?eigenvalues
%?
%?See?also:
%???kernel_matrix?RBF_kernel?demo_fixedsize

%?Copyright?（c）?2002??KULeuven-ESAT-SCD?License?&?help?@?http://www.esat.kuleuven.ac.be/sista/lssvmlab


[Ndim]?=?size（X）;
[Ncdim]?=?size（Xs）;

eval（‘type;‘‘type=‘‘eig‘‘;‘）;
if?~（strcmp（type‘eig‘）?|?strcmp（type‘eigs‘）?|?strcmp（type‘eign‘））
??error（‘Type?needs?to?be?‘‘eig‘‘?‘‘eigs‘‘?or?‘‘eign‘‘...‘）;
end
??

%?eigenvalue?decomposition?to?do..
if?nargin<=6
??omega?=?kernel_matrix（Xs?kernel?kernel_pars）;
??if?strcmp（type‘eig‘）
????[eigveceigvals]?=?eig（omega+2*eye（size（omega1）））;?%?+?jitter?factor
????eigvals?=?diag（eigvals）;
??elseif?strcmp（type‘eigs‘）
????eval（‘nb;‘‘nb=min（size（omega1）10）;‘）;
????[eigveceigvals]?=?eigs（omega+2*eye（size（omega1））nb）;?%?+?jitter?factor
??elseif?strcmp（type‘eign‘）
????eval（‘nb;‘‘nb=min（size（omega1）10）;‘）;
????[eigveceigvals]?=?eign（omega+2*eye（size（omega1））nb）;?%?+?jitter?factor
??end
??eigvals?=?（eigvals-2）/Nc;
??peff?=?eigvals>eps;
??eigvals?=?eigvals（peff）;
??eigvec?=?eigvec（:peff）;
end
??
%?Cmex
features?=?phitures（Xs‘X‘eigveceigvalskernel?kernel_pars）;

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----

?????文件???????2738??2003-02-21?22:39??LS_SVMlab\AFE.m

?????文件??????20200??2009-04-16?21:24??LS_SVMlab\all0416.mat

?????文件????????572??2009-03-28?16:15??LS_SVMlab\alphaandb.m

?????文件???????5785??2003-02-21?22:39??LS_SVMlab\bay_errorbar.m

?????文件???????2003??2003-02-21?22:39??LS_SVMlab\bay_initlssvm.m

?????文件??????10345??2003-02-21?22:39??LS_SVMlab\bay_lssvm.m

?????文件???????8187??2003-02-21?22:39??LS_SVMlab\bay_lssvmARD.m

?????文件???????9358??2003-02-21?22:39??LS_SVMlab\bay_modoutClass.m

?????文件???????5977??2003-02-21?22:39??LS_SVMlab\bay_optimize.m

?????文件???????4178??2003-02-21?22:39??LS_SVMlab\bay_rr.m

?????文件????????164??2005-04-15?21:53??LS_SVMlab\buffer.mc

?????文件???????5632??2003-02-21?22:39??LS_SVMlab\changelssvm.m

?????文件???????4245??2005-04-15?19:10??LS_SVMlab\code.asv

?????文件???????4245??2005-04-15?19:11??LS_SVMlab\code.m

?????文件???????2118??2003-02-21?22:39??LS_SVMlab\codedist_bay.m

?????文件????????756??2003-02-21?22:39??LS_SVMlab\codedist_hamming.m

?????文件???????2018??2003-02-21?22:39??LS_SVMlab\codedist_loss.m

?????文件???????4125??2003-02-21?22:39??LS_SVMlab\codelssvm.m

?????文件???????5197??2003-02-21?22:39??LS_SVMlab\code_ECOC.m

?????文件????????550??2003-02-21?22:39??LS_SVMlab\code_MOC.m

?????文件????????364??2003-02-21?22:39??LS_SVMlab\code_OneVsAll.m

?????文件????????555??2003-02-21?22:39??LS_SVMlab\code_OneVsOne.m

?????文件????????734??2009-03-28?16:26??LS_SVMlab\compufun.m

?????文件?????????32??2003-03-20?09:24??LS_SVMlab\Contents.m

?????文件???????8174??2003-02-21?22:39??LS_SVMlab\crossvalidate.m

?????文件????????757??2009-04-19?09:01??LS_SVMlab\data0419.mat

?????文件???????1011??2008-12-11?19:36??LS_SVMlab\datatest.mat

?????文件???????1606??2008-12-11?19:26??LS_SVMlab\datatrain.mat

?????文件???????1886??2003-02-21?22:39??LS_SVMlab\deltablssvm.m

?????文件???????3369??2003-02-21?22:39??LS_SVMlab\democlass.m

............此處省略83個文件信息