資源簡介
現有的LSSVM工具箱,自帶PSO優化,參數無需調整,Matlab編寫的人工蜂群算法代碼,含詳細注釋和測試函數,簡短易懂,執行順暢。可用于解決無約束優化問題。

代碼片段和文件信息
function?[featureseigveceigvals]?=?AFEm(Xskernel?kernel_parsXtypenbeigveceigvals)
%?Automatic?Feature?Extraction?by?Nystrom?method
%
%
%?>>?features?=?AFE(X?kernel?sig2?Xt)
%
%?Description
%?Using?the?Nystr?m?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?m‘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)?2011??KULeuven-ESAT-SCD?License?&?help?@?http://www.esat.kuleuven.be/sista/lssvmlab
N?=?size(X1);
Nc?=?size(Xs1);
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<=7
??omega?=?kernel_matrix(Xs?kernel?kernel_pars);
??if?strcmp(type‘eig‘)
????[eigveceigvals]?=?eig(omega+2*eye(size(omega1)));?%?+?jitter?factor
????eigvals?=?diag(eigvals);?
????clear?omega
??elseif?strcmp(type‘eigs‘)
????eval(‘nb;‘‘nb=min(size(omega1)10);‘);?options.disp?=?0;
????[eigveceigvals]?=?eigs(omega+2*eye(size(omega1))nb‘lm‘options);?clear?omega?%?+?jitter?factor
??elseif?strcmp(type‘eign‘)
????eval(‘nb;‘‘nb=min(size(omega1)10);‘);?
????[eigveceigvals]?=?eign(omega+2*eye(size(omega1))nb);?clear?omega?%?+?jitter?factor
??end
??eigvals?=?(eigvals-2)/Nc;
??peff?=?eigvals>eps;
??eigvals?=?eigvals(peff);
??eigvec?=?eigvec(:peff);?clear?peff
??
end?
if?strcmp(kernel‘RBF_kernel‘)
????omegaN?=?sum(X.^22)*ones(1Nc);
????omegaN?=?omegaN?+?ones(N1)*sum(Xs.^22)‘;
????omegaN?=?omegaN?-2*X*Xs‘;?clear?X?Xs
????omegaN?=?exp(-o
?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????目錄???????????0??2015-10-30?17:06??LSSVMlabv1_8_R2009b_R2011a\
?????文件????????3437??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\AFEm.m
?????文件?????????603??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\MLP_kernel.m
?????文件????????1105??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\RBF_kernel.m
?????文件????????5785??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\bay_errorbar.m
?????文件????????1998??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\bay_initlssvm.m
?????文件???????10339??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\bay_lssvm.m
?????文件????????8187??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\bay_lssvmARD.m
?????文件????????9358??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\bay_modoutClass.m
?????文件????????5843??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\bay_optimize.m
?????文件????????4312??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\bay_rr.m
?????文件????????1479??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\bitreverse32.m
?????文件????????5576??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\changelssvm.m
?????文件????????4744??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\cilssvm.m
?????文件????????4245??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\code.m
?????文件????????5194??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\code_ECOC.m
?????文件?????????548??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\code_MOC.m
?????文件?????????361??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\code_OneVsAll.m
?????文件?????????576??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\code_OneVsOne.m
?????文件????????2107??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\codedist_bay.m
?????文件?????????753??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\codedist_hamming.m
?????文件????????2015??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\codedist_loss.m
?????文件????????4126??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\codelssvm.m
?????文件????????5847??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\crossvalidate.m
?????文件????????3941??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\crossvalidatelssvm.m
?????文件????????3188??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\csa.m
?????文件????????2251??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\demo_fixedclass.m
?????文件????????3233??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\demo_fixedsize.m
?????文件????????3447??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\demo_yinyang.m
?????文件????????3461??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\democlass.m
?????文件????????2147??2015-09-29?17:30??LSSVMlabv1_8_R2009b_R2011a\democonfint.m
............此處省略52個文件信息
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