Paper available on Hybrid Classification

[Dr. Michael Wong]

FTP-host: physics.ust.hk
FTP-file: pub/kymwong/hybrid.ps.gz

The following paper, presented at IWANNT*95, 
is now available via anonymous FTP. (8 pages long)
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         A Hybrid Expert System for Error Message Classification

                  H.C. Lau, K.Y. Szeto, K.Y.M. Wong
                       Department of Physics, 
         The Hong Kong University of Science and Technology,
                 Clear Water Bay, Kowloon, Hong Kong.
     E-mail address: phhclau at usthk.ust.hk, phkywong at usthk.ust.hk

                                and

                            D.Y. Yeung
                   Department of Computer Science, 
         The Hong Kong University of Science and Technology,
                 Clear Water Bay, Kowloon, Hong Kong.


                               ABSTRACT

A hybrid intelligent classifier is built for pattern classification. 
It consists of a classification and regression tree (CART), a genetic
algorithm (GA) and a neural network (NN).  CART extracts features of 
the patterns by setting up decision rules.  Rule improvement by GA is 
explored.  The rules act as a pre-processing layer of NN, a multi-
class neural classifier, through which the most probable class is 
determined.  A realistic test of classifying error messages generated 
from a telephone exchange shows that the CART-NN hybrid system has
comparable performance with Bayesian neural network.

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FTP instructions:

unix> ftp physics.ust.hk
Name: anonymous
Password: your full email address
ftp> cd pub/kymwong
ftp> get hybrid.ps.gz
ftp> quit
unix> gunzip hybrid.ps.gz
unix> lpr hybrid.ps