I have a set of matrices which should fall into 3 distinct set/groups/clusters. They are unlabelled. I wish to do unsupervised clustering with PCA. I am using matlab as well. At the end I would also like to examine the eigenvectors.
Matlab has a function call "princomp" which I believe can do this task; is this correct?
When I give "princomp" a matrix the output can be interpreted how?
For example:
dataTmp=[1 1; 2 2; 1 2; 2 3; 4 6; -1 1; -2 2; -4 3; -5 8] dataTmp = 1 1 2 2 1 2 2 3 4 6 -1 1 -2 2 -4 3 -5 8 princomp(dataTmp) ans = 0.9207 0.3902 -0.3902 0.9207
or should I being using the function "zscore" beforehand to standardise the values first?
princomp(zscore(dataTmp)) ans = 0.7071 0.7071 -0.7071 0.7071
How do I interpret the answer? The data I made were simple points in either the first or second quandrant.