Data modeling using constrained categorical regression

Harvey L. Bodine; Steven S. Henley; Robert L. Dawes; Richard M. Golden; T. Michael Kashner

Data modeling using constrained categorical regression

Harvey L. Bodine, Steven S. Henley, Robert L. Dawes, Richard M. Golden, T. Michael Kashner

Medicine

Research output: Contribution to journal › Article › peer-review

Abstract

We apply a sparsely-connected neural network to the problem of recognizing statistical regularities and patterns in a National Labor and Alcohol Survey database. The network architecture, called Constrained Categorical Regression (CCR), is designed to identify valid statistical inferences even in the presence of a mis-specified model and offers fast training with guaranteed convergence. Each weight within the network can be tested for statistical significance and the overall network is interpretable for meaning and validity.

Original language	English
Pages (from-to)	1033-1038
Number of pages	6
Journal	Intelligent Engineering Systems Through Artificial Neural Networks
Volume	6
State	Published - 1996

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Data modeling using constrained categorical regression

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