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From: argray@otago.ac.nz
Subject: Multicollinearity in input data
Message-ID: <1994Nov24.180600.1@otago.ac.nz>
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Organization: University of Otago, Dunedin, New Zealand
Date: Thu, 24 Nov 1994 05:06:00 GMT

Hello everyone,

	I am currently using a back propagation neural network to estimate 
software effort based on complexity indicators.  I am interested in the 
effects of some of the input data being multicollinear.  The existence of 
multicollinearity can be identified using standard statistical techniques and 
common sense about the nature of the data.  Is it better if I only use 
uncorrelated inputs or can the network handle the correlations?
	I have not been able to find any references to this problem and would
appreciate any assistance in finding references or advice in solving the
problem.
	Please reply by email and if there is sufficient interest then I will 
post a summary to the group.

Thanks in advance,
Andrew
