fwlsmm_demo.m

加权最小二乘法&最大最小化优化算法 weighted least-squares + weighted min-max optimization

% Demonstration for FWLSMM. Obtain error plot when beta varies from 0 to 1

clear all;

options = optimset('algorithm', 'active-set', 'MaxFunEvals', 200, 'Display', 'iter');

lambda = 0:0.1:1;
els = zeros(size(lambda));
emm = zeros(size(lambda));
i = 1;
for a = lambda,
%     K.beta = a;
%     [x, fval] = fwlsmm(@testc, [0; 0], @testnlcon, K, options);
    [x, fval] = fwlsmm(@egCostFunc, [0; 0], a, [], [], [], [], [], [], [], [], @egNlcon, options);
    e = egCostFunc(x);
    
    els(i) = sum(e)/length(e);
    emm(i) = max(e);
    i = i + 1;
end;

plot3(els, emm, 0:0.1:1);
xlabel('LS error');
ylabel('MM error');
zlabel('\lambda');
grid on;