Message-ID: <1303425366704-3467015.post@n4.nabble.com>
Date: 2011-04-21T22:36:06Z
From: psycrcyo
Subject: Rearranging PCA results from R
Hi!!
I'm having trouble selecting 10 out of 41 attributes of the KDD data set. In
order to identify the components with the higher variance I'm using
princomp. the result i get for summary(pca1) is:
Comp.1 Comp.2 Comp.3
Comp.4 Comp.5 Comp.6 Comp.7 Comp.8
Comp.9 Comp.10
Standard deviation 9.882181e+05 3.303966e+04 7.083767e+02
3.282215e+02 9.839173e+01 4.642758e+01 2.923245e+01 6.447245e+00
2.689471e+00 1.292525e+00
Proportion of Variance 9.988828e-01 1.116555e-03 5.132601e-07
1.101902e-07 9.902073e-09 2.204758e-09 8.740565e-10 4.251648e-11
7.398482e-12 1.708784e-12
Cumulative Proportion 9.988828e-01 9.999994e-01 9.999999e-01 1.000000e+00
1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00
1.000000e+00
and for the loadings a constant 0.024 for the proportion of variability:
Comp.1 Comp.2 Comp.3 Comp.4 Comp.5 Comp.6 Comp.7 Comp.8
Comp.9 Comp.10
SS loadings 1.000 1.000 1.000 1.000 1.000 1.000 1.000
1.000 1.000 1.000
Proportion Var 0.024 0.024 0.024 0.024 0.024 0.024 0.024
0.024 0.024 0.024
Cumulative Var 0.024 0.048 0.071 0.095 0.119 0.143 0.167
0.190 0.214 0.238
So the questions are: Which of the two is the right proportion of variance?
and, is there a way for R to tell me which attributes they belong to?
Any help will be very appreciated.
psycrcyo
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