sfam_demo(原始底版文件).m

实现遗传算法对于SFAM网络输入模式的序列优化

% SFAM usage demo. 
%function [sol,val]=sfam_demoEval(sol,options)

% load data
load trainTestData2
load StageOneIris

trainTestData=cell(1,20);
trainTestLabel=cell(1,20);
A=zeros(20,75);
for i=1:20
    A(i,:)=randperm(75)
    trainTestData{1,i}=traindata(A(i,:),:);
    trainTestLabel{1,i}=trainlabel(A(i,:));
    % create network
    net = create_network(size(trainTestData{1,i},2));

    % change some parameters as you wish
    net.epochs = 100;

    % train the network
    tnet = train(trainTestData{1,i}, trainTestLabel{1,i}, net, 100);

    % test the network on the testdata
    r = classify(testdata1, tnet, testlabel1, 100);

    % compute classification performance
    elapsed = toc;
    fprintf(1,'Chromosome hit rate: %f\tElapsed %.2f seconds.\n', sum(r' == testlabel1)*100/size(testdata1,1),elapsed)
    tic;
end