Re: [R] Rearranging PCA results from R

From: Uwe Ligges <ligges_at_statistik.tu-dortmund.de>
Date: Fri, 22 Apr 2011 12:31:38 +0200

On 22.04.2011 00:36, psycrcyo wrote:
> 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:

Actually you calculated the first 10 principal components. You have not selected anything - particularly no "attributes", all "attributes" are included in your 10 first PCs. I'd suggest to read some textbook about PCA.

Some people like to perform stepwise regression of variables on the first PC if it explains a lot of the variance, but that should be done *very* carefully, if at all.

Best,
Uwe Ligges

>
>
> 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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>
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https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Fri 22 Apr 2011 - 10:37:02 GMT

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