Monash FCIT AI Consortium (MAIC)
  Faculty of Computing and Information Technology, Monash University

                  * * *  Seminar Announcement  * * *

    "DECISION TREES AND VARIABLE VALUED LOGIC RULES: A COMPARISON"

                            Dr. Xindong Wu
                   Software Development Dept, Monash
                   (xindong@insect.sd.monash.edu.au)

                   Wednesday 26 July 1995 at 2.00 pm
          Room F6.47, 900 Dandenong Road, Caulfield East 3145

Abstract
========

Decision trees  and variable valued logic  rules have both been widely
used in machine learning, especially  in attribute-based induction, in
which examples are described  using a fixed collection  of attributes.
This talk analyses the  advantages  and disadvantages of the  decision
tree based  learning  algorithms (such as  ID3,  NewID and C4.5),  and
compares these  algorithms   with  the   author's own  HCV   induction
algorithm, which generates   rules  in  variable  valued  logic.    In
addition  to theoretical  analysis, the   talk provides  a  battery of
experimental results showing that the rules generated  by HCV are more
compact  and more accurate than the  decision trees (or decision rules
derived from the decision   trees) produced by ID3-like  algorithms in
both artificial and real world  domains.  Peter Jackson (1990) claimed
that the  reason many people use  decision trees rather  than rules is
that the  ID3-like    algorithms  are  simpler   than   other learning
algorithms.  This  talk   will demonstrate that  that   argument is no
longer convincing.

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The MAIC seminar series is free and open to everyone.
Enquiries to: maic-request@fcit.monash.edu.au
URL: http://www.cs.monash.edu.au/~korb/maic-calendar.html