% a warmup makeup exercise for you Assignment1
% makeup dataset in 2D

x = [1 1; 1 2; 2 1; -1 -1; -1 -2];

plot(x(:,1), x(:,2), 'kx')  %plots the points

axis ([-3 3 -3 3])

text (x(:,1) +.1, x(:,2)+.1, '1|2|3|4|5'); %adds labels to points
% How many clusters can you visually see?

%find the Euclidean distance using pdist

ye = pdist(x, 'euclid');

% put distances in a matrix form

ye_mat = squareform(ye);

% You may wish to display this matrix to visually display
% Note that this matrix is square and symmetric 

% read about a few other metric for distance calculation such as cityblock

ycb = pdist (x , 'cityblock');
ycb_mat = squareform (ycb);


zsingle = linkage (ye, 'single');
zcomplete = linkage (ye, 'complete');

dendrogram(zsingle)
title ('clustering single linkage')

dendrogram(zcomplete)
title ('clustering complete linkage')