x = [
normrnd(0,1,[1,1000]) normrnd(5,2,[1,1000]) normrnd(-5,1,[1,1000]);
normrnd(1,1,[1,1000]) normrnd(-3,3,[1,1000]) normrnd(8,1,[1,1000])
];
t = [ones(1,1000) 2*ones(1,1000) 3*ones(1,1000)];
ri = randperm(length(x));
x = x(:,ri);
t = t(ri);
t = full(ind2vec(t));
for i = 1:3
idx = vec2ind(t) == i;
scatter(x(1,idx), x(2,idx), 'filled');
hold on;
end
hold off;

net = feedforwardnet(1000);
net = configure(net, x, t);

for z = 1:1000

    y1 = net(x);
    subplot(1,2,1);
    for i = 1:3
    idx = vec2ind(t) == i;
    scatter(x(1,idx), x(2,idx), 'filled');
    hold on;
    end
    hold off;
    title('Dataset');
    subplot(1,2,2);
    for i = 1:3
    idx = vec2ind(y1) == i;
    scatter(x(1,idx), x(2,idx), 'filled');
    hold on;
    end
    hold off;
    title('Pre-training');
end
net = train(net, x, t);

y2 = net(x);
subplot(1,3,1);
for i = 1:3
idx = vec2ind(t) == i;
scatter(x(1,idx), x(2,idx), 'filled');
hold on;
end
hold off;
title('Dataset');
subplot(1,3,2);
for i = 1:3
idx = vec2ind(y1) == i;
scatter(x(1,idx), x(2,idx), 'filled');
hold on;
end
hold off;
title('Pre-training');
subplot(1,3,3);
for i = 1:3
idx = vec2ind(y2) == i;
scatter(x(1,idx), x(2,idx), 'filled');
hold on;
end
hold off;
title('Post-training');