kmeans

Hi there,

how to write the plot if i use 4 cluster like this:

X = [randn(100,2)+ones(100,2);... randn(100,2)-ones(100,2)]; opts = statset('Display','final'); [idx,ctrs] = kmeans(X,4,... 'Distance','city',... 'Replicates',5,... 'Options',opts); plot(X(idx==1,1),X(idx==1,2),'r.','MarkerSize',12) hold on plot(X(idx==2,1),X(idx==2,2),'b.','MarkerSize',12) [plot ....] [plot ....]

thank you

Answer 1

[Wayne King]

You do the same thing except:

    plot(X(idx==1,1),X(idx==1,2),'r.','MarkerSize',10);
    hold on
    plot(X(idx==2,1),X(idx==2,2),'b.','MarkerSize',10);
    plot(X(idx==3,1),X(idx==3,2),'g.','MarkerSize',10);
    plot(X(idx==4,1),X(idx==4,2),'k.','MarkerSize',10);

[Isabella Osetinsky-Tzidaki]

add

>> hold off

[yoga z]

thank u very much for your answer

Answer 2

[Kawther]

Thank you Wayne King. I did get benefit from your code. i want to ask please about finding the bet error rate for such a code. How can i determine the decision regions, so that i can then find the bet error rate?

Can i consider the originally sent data as a training data and resend data again and consider it and a test data and use them to find the bet error rate?

Thank you very much. Kawther Hamad,