%Eexample2.m
%example 2 for elinkage, requires Statistics Toolbox

load carsmall

y = [Cylinders, Displacement, Horsepower, Weight, Acceleration];

%remove observations with missing values
[miss1, miss2] = find(isnan(y));
y(miss1, :) = [];
Model(miss1,:) = [];
n = size(y, 1);
N = n;   %cluster the first N obs.

x = y(1:N, :);
lab = Model(1:N, 1:4);

%standardize the data (optional)
y = zscore(y);  
dst = pdist(y);

%elinkage with alpha=1, Euclidean distance
%by default, dendrogram plots highest 30 nodes
L = elinkage(dst, 1);
dendrogram(L);
cl = cluster(L, 'MaxClust', 4);
[lab cl]

%or we can plot logs of heights, easier to read
L(:, 3) = log(1 + L(:, 3));
dendrogram(L, 15);  %15 nodes are plotted

%elinkage with alpha=2, squared distances
%compare with alpha=1
L2 = elinkage(dst, 2);
A = [L(:,1:2) L2(:,1:2)]