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.