sfam_demoeval.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)

%global traindata
%global trainlabel
global StageOneIris

load StageOneIris
% load data
 sol;
 numvars=size(sol,2)-1;
    % create network
    net = create_network(size(traindata(sol(1:numvars),:),2));

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

    % train the network
    tnet = train(traindata(sol(1:numvars),:), trainlabel(sol(1:numvars)), net, 100);

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

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