load regressionData.mat; output = output';

%划分数据集 [value,index] = sort(rand(1,2000)); x_train = input(index(1:1800),:); x_test = input(index(1801:2000),:); y_train = output(index(1:1800),:); y_test = output(index(1801:2000),:);

%PSO参数 c1 = 2;       %PSO局部搜索能力 c2 = 2;       %PSO全局搜索能力 sizepop = 20; %种群规模 k = 100;      %最大迭代次数 w = 0.9       %惯性因子

%确定优化参数的数目 length = 2; param = rand(sizepop,length); speed = rand(sizepop,length); popmin = 0.01; popmax = 100; vmin = -1; vmax = 1;

for i=1:sizepop     gamma = param(i,1);     sig2 = param(i,2);     [alpha,b] = trainlssvm({x_train,y_train,'function estimation',gamma,sig2,'RBF_kernel'