reverse engineering principal components...
- To: mathgroup at smc.vnet.net
- Subject: [mg128396] [mg128396] reverse engineering principal components...
- From: Richard Palmer <rhpalmer at gmail.com>
- Date: Fri, 12 Oct 2012 00:02:07 -0400 (EDT)
- Delivered-to: l-mathgroup@mail-archive0.wolfram.com
- Delivered-to: l-mathgroup@wolfram.com
- Delivered-to: mathgroup-newout@smc.vnet.net
- Delivered-to: mathgroup-newsend@smc.vnet.net
I would like to be able to take a large dataset, compute the principal
components on a sufficient subset, and use the results to compute principal
components on the remaining observations. So far, I haven't been able to
figure out how it is done. Here is sample code (computed as a notebook
expression). Can anyone tell me where I am going wrong?
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Cell["\<\
make a table of data and a table of the principal components using \
the Correllation method. Check to see that they have the requisite \
properties\
\>", "Text",
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Standardize the observations and compute a correlation matrix. \
Compute the eigenvectors.\
\>", "Text",
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I think this is the multiplication. However, the variances are not \
correct since they do not decrease.\
\>", "Text",
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--
Richard Palmer
Home 941 412 8828
Cell 508 982-7266