How to improve the distance calculation on two separated datasets

Hi,

Can anyone advice me on how to improve the distance calculation on the 2 separated datasets? My Data:

X = [   3.6  79
        1.8  54
        3.333  74
        2.283  62
        4.533  85
        2.883  55
        4.7  88
        3.6  85
        1.95  51
        4.35  85
        1.833  54
        3.917  84
        4.2  78
        1.75  47
        4.7  83
        2.167  52
        1.75  62
        4.8  84
        1.6  52
        4.25  79
        1.8  51
        1.75  47
        3.45  78
        3.067  69
        4.533  74
        3.6  83
        1.967  55
        4.083  76
        3.85  78
        4.433  79
        4.3  73
        4.467  77
        3.367  66
        4.033  80
        3.833  74
        2.017  52
        1.867  48
        4.833  80
        1.833  59
        4.783  90  ]

    clc;  
    close all; 
    figure;
    h(1) = plot(X(:,1),X(:,2),'bx');
    hold on;

    X1 = X(1:3,:);
    X2 = X(4:40,:);

    h(2) = plot(X1(1:3,1), X1(1:3,2),'rs','MarkerSize',10);
    k=5;
    [D2 ind] = sort(squeeze(sqrt(sum(bsxfun(@minus,X2,permute(X1,[3 2 1])).^2,2))))
    ind_closest = ind(1:k,:)
    x_closest = X(ind_closest,:)
    for j = 1:length(x_closest);
        h(3) =plot(x_closest(j,1),x_closest(j,2),'ko','MarkerSize',10);
    end

The output shown as in the picture:

The problem is, the code does not picks the closest data points of red squared data points.

[Image Analyst]

Too bad. You forgot to attach 'faithful.csv' so now you'll have to wait even longer for an answer.

In the meantime, take a look at pdist2() if you have the Statistics and Machine Learning Toolbox.

[amj]

Dear Image Analyst,

I really do apologize for the data. Attached is the data