fsals_svmbench1.m

崭新矢量机SVM源码

clear
load blfmnist;

% [samples,A,B]     =  scaletrain1(mnistsamples);
% labels            =  mnistlabels;
% testsamples       =  scaletest1(mnistsamples,A,B);
% testlabels        =  mnistlabels;

samples = mnistsamples;
labels  = mnistlabels;
testsamples = mnisttestsamples;
testlabels  = mnisttestlabels;


if length(unique(mnistlabels)) == 2
    labels = (labels > 0) + 1;
    testlabels = (testlabels > 0) + 1;
end
clear mnistsamples mnisttestsamples;

kernel = 'rbf';
param = 2^-6;
func= 'pfsals_svm';
lamdavec = 2.^linspace(-1,-1,1); 
% Q = randperm(length(labels));
for i = 1:length(lamdavec);
%     starttime = cputime;
%     Q = Q(1:600);
%     [alpha,bias,svi,sv]         = onevsalltrain(samples,labels,kernel,param,lamdavec(i),Q,func,[]);
%     endtime = cputime;
%     [result,vote]               = onevsalltest(testsamples,testlabels,samples,labels,kernel,param,alpha,svi,bias,func,[]);
%     
%     for j = 1:length(unique(mnistlabels))
%         tempnsv(j,1) = length(svi{j});
%     end
    tic;
    [alpha,bias,svi,sv]         = onevsalltrain(samples,labels,kernel,param,lamdavec(i),0.4,func);
    endtime = toc;
    [result,vote]               = onevsalltest(testsamples,testlabels,samples,labels,kernel,param,alpha,svi,bias,func);
    
    nsv(i,1) = sv;
	correctvec(i,1) = mean(result == testlabels);
    timevec(i,1) = endtime;
    fprintf('Support vector = %f\n',nsv(i,1));
	fprintf('Accuracy = %f\n',correctvec(i,1));
    fprintf('Time = %f\n',timevec(i,1));
end
% plot(log2(lamdavec'),correctvec,'*-r');
% figure(2);
% plot(log2(lamdavec'),nsv,'*-r');