**Subject: **Re: Please help in Neural Network Implementaion !!

**From: **Chin Wei Chuen (*eng60235@nus.edu.sg*)

**Date: **Tue Feb 01 2000 - 16:54:43 MET

**sorted by:**[ date ] [ thread ] [ subject ] [ author ]**Next message:**cindy mason: "no title"**Previous message:**Bob Abrahart: "GeoComputation 2000 - Call for Papers"**Next in thread:**Chin Wei Chuen: "Re: Please help in Neural Network Implementaion !!"

What you are doing interests me very much. I'd like to know more details

of your experiment. Please read my inserted comments below carefully. I

hope I can provide you with some helpful comments later. Thanks!

Joe Smith wrote:

*> Hi,
*

*>
*

*> I'm interested in developing a neural network in Perl. I've read
*

*> the FAQs on this group as well as many of the resources it points
*

*> to and most of the messages of the past month or so .. however
*

*> I still don't understand how to take it from theory to practice.
*

*>
*

*> Let me explain what I would like to use it for and what I'm currently
*

*> doing:
*

*>
*

*> I have to process thousands of matrices of 25 - 40 predictors or
*

*> independent variables (columns) and 500 or so cases (rows) and 1
*

*> dependent or desired output vector (column) corresponding to each
*

*> case.
*

*>
*

*> 1) This matrix is a result of a factorial analysis (principal
*

*> components analysis and data dimensionally reduction functions)
*

*> by means of Jacobi transformations. Basically I created a series
*

*> of matrices based on clusters of common variance of the original
*

*> sample data.
*

How did you do the Jacobi transformation.

What are these matrices?

You said that you did a factorial analysis; how are the 'clusters of

common variance' related it?

*>
*

*>
*

*> 2) I calculate a multi-variate regression analysis on these
*

*> matrices using matrix algebra to create a series of weights that
*

*> allow me to predict y given X (y(j)=b(0)+b(1)x(1)+ .. +b(k)x(n)).
*

*> This procedure gives me good results with an average adjusted multiple
*

*> correlation coefficient of 0.9987
*

How is the 'average multiple correlation coeff' calculated?

*>
*

*>
*

*> My problem lies in the fact that I need to crunch every matrix
*

*> individually in order to predict them even though all the matrices
*

*> are a product of the same process and I should be able to predict
*

*> all of them by processing just one matrix the beta weights that
*

*> result from the analysis are different for every matrix. As you
*

*> can imagine this calculations take for ever and are not easy to
*

*> parallelize since they are always dependent on the previous step.
*

What are you trying to predict? The correlation coeffs between your

predictors or something else?

*>
*

*>
*

*> I would like to know from you folks in this group, what kind of NN
*

*> would best suit this problem, that would learn how to solve all the
*

*> matrices without having to crunch all the matrices and that would do
*

*> this in parallel rather than a serial manner.
*

It's hard to answer this question unless you're more specific about your

goal.

*>
*

*>
*

*> If I understand the information I've gather on this group and on
*

*> the FAQs there a several types of network designs, I would imagine
*

*> that we would need a probabilistic approach to this problem, perhaps
*

*> using Bayesian inference to unify the results into a common set of
*

*> weights by calculating the similarities of the matrices and their
*

*> corresponding weights.
*

*>
*

*> Please help ...
*

*>
*

*> Thank you,
*

*>
*

*> Joe Smith
*

*> jsmith@currentreviews.com
*

############################################################################

This message was posted through the fuzzy mailing list.

(1) To subscribe to this mailing list, send a message body of

"SUB FUZZY-MAIL myFirstName mySurname" to listproc@dbai.tuwien.ac.at

(2) To unsubscribe from this mailing list, send a message body of

"UNSUB FUZZY-MAIL" or "UNSUB FUZZY-MAIL yoursubscription@email.address.com"

to listproc@dbai.tuwien.ac.at

(3) To reach the human who maintains the list, send mail to

fuzzy-owner@dbai.tuwien.ac.at

(4) WWW access and other information on Fuzzy Sets and Logic see

http://www.dbai.tuwien.ac.at/ftp/mlowner/fuzzy-mail.info

(5) WWW archive: http://www.dbai.tuwien.ac.at/marchives/fuzzy-mail/index.html

**Next message:**cindy mason: "no title"**Previous message:**Bob Abrahart: "GeoComputation 2000 - Call for Papers"**Next in thread:**Chin Wei Chuen: "Re: Please help in Neural Network Implementaion !!"

*
This archive was generated by hypermail 2b25
: Thu Apr 06 2000 - 15:59:41 MET DST
*