function [BestCVaccuracy,Bestc,Bestg,ga_option,model,fit_gen] = gaSVMcgForClass(train_label,train_data)
% gaSVMcgForClass
%%
% by faruto
%Email:patrick.lee@foxmail.com QQ:516667408 http://blog.sina.com.cn/faruto BNU
%last modified 2010.01.17
%% 若转载请注明：
% faruto and liyang , LIBSVM-farutoUltimateVersion
% a toolbox with implements for support vector machines based on libsvm, 2009.
%
% Chih-Chung Chang and Chih-Jen Lin, LIBSVM : a library for
% support vector machines, 2001. Software available at
% http://www.csie.ntu.edu.tw/~cjlin/libsvm
%% 参数初始化
if nargin == 2
ga_option = struct('maxgen',20,'sizepop',20,'ggap',0.9,...
'cbound',[0,100],'gbound',[0,1000],'v',5);
end
% maxgen:最大的进化代数,默认为200,一般取值范围为[100,500]
% sizepop:种群最大数量,默认为20,一般取值范围为[20,100]
% cbound = [cmin,cmax],参数c的变化范围,默认为(0,100]
% gbound = [gmin,gmax],参数g的变化范围,默认为[0,1000]
% v:SVM Cross Validation参数,默认为5
%%
MAXGEN = ga_option.maxgen;
NIND = ga_option.sizepop;
NVAR = 2;
PRECI = 20;
GGAP = ga_option.ggap;
trace = zeros(MAXGEN,2);
FieldID = ...
[rep([PRECI],[1,NVAR]);[ga_option.cbound(1),ga_option.gbound(1);ga_option.cbound(2),ga_option.gbound(2)]; ...
[1,1;0,0;0,1;1,1]];
Chrom = crtbp(NIND,NVAR*PRECI);
v = ga_option.v;
%%
cg = bs2rv(Chrom,FieldID);
for nind = 1:NIND
cmd = ['-v ',num2str(v),' -c ',num2str(cg(nind,1)),' -g ',num2str(cg(nind,2))];
ObjV(nind,1) = svmtrain(train_label,train_data,cmd);
end
[BestCVaccuracy,I] = max(ObjV);
Bestc = cg(I,1);
Bestg = cg(I,2);
fit_gen(1,MAXGEN)=0;
%%
%while 1
for gen = 1:MAXGEN
FitnV = ranking(-ObjV);
SelCh = select('sus',Chrom,FitnV,GGAP);
SelCh = recombin('xovsp',SelCh,0.7);
SelCh = mut(SelCh);
cg = bs2rv(SelCh,FieldID);
for nind = 1:size(SelCh,1)
cmd = ['-v ',num2str(v),' -c ',num2str(cg(nind,1)),' -g ',num2str(cg(nind,2))];
ObjVSel(nind,1) = svmtrain(train_label,train_data,cmd);
end
[Chrom,ObjV] = reins(Chrom,SelCh,1,1,ObjV,ObjVSel);
if max(ObjV) <= 50
continue;
end
[NewBestCVaccuracy,I] = max(ObjV);
cg_temp = bs2rv(Chrom,FieldID);
temp_NewBestCVaccuracy = NewBestCVaccuracy;
if NewBestCVaccuracy > BestCVaccuracy
BestCVaccuracy = NewBestCVaccuracy;
Bestc = cg_temp(I,1);
Bestg = cg_temp(I,2);
end
if abs( NewBestCVaccuracy-BestCVaccuracy ) <= 10^(-2) && ...
cg_temp(I,1) < Bestc
BestCVaccuracy = NewBestCVaccuracy;
Bestc = cg_temp(I,1);
Bestg = cg_temp(I,2);
end
trace(gen,1) = max(ObjV);
trace(gen,2) = sum(ObjV)/length(ObjV);
fit_gen(gen)=BestCVaccuracy;
% if gen <= MAXGEN/2
% continue;
% end
% if BestCVaccuracy >=80 && ...
% ( temp_NewBestCVaccuracy-BestCVaccuracy ) <= 10^(-2)
% break;
% end
if gen == MAXGEN
break;
end
end
cmd_temp = ['-c ',num2str( Bestc ),' -g ',num2str( Bestg)];
model = svmtrain(train_label, train_data, cmd_temp);
评论1