Try kmeans with 10 classes, and operating on the d values:
data = rand(100, 4)
x = data(:, 1);
y = data(:, 2)
z = data(:, 3);
d = data(:, 4);
numClasses = 10
% Find classes based on 4th column.
indexes = kmeans(d, numClasses);
% Make up a colormap with 10 colors
cmap = jet(10);
% Assign a color to each data point based on it's class
markerColors = zeros(10, 3); % 10 colors.
for k = 1 : size(data, 1)
thisClassNumber = indexes(k)
markerColors(k, :) = cmap(thisClassNumber, :);
end
scatter3(x, y, z, 50, markerColors, 'filled');
fontSize = 20;
xlabel('X', 'FontSize', fontSize);
ylabel('Y', 'FontSize', fontSize);
zlabel('Z', 'FontSize', fontSize);
There is a marker at each (x,y,z) location and its color depends on which of the 10 classes that point's "d" value got classified into.
