Newsgroups: comp.ai.jair.announce
Path: cantaloupe.srv.cs.cmu.edu!rochester!udel!news.mathworks.com!newsfeed.internetmci.com!news.msfc.nasa.gov!pendragon!ames!eos!kronos.arc.nasa.gov!jair-ed
From: jair-ed@ptolemy.arc.nasa.gov
Subject: New Article, Rule-based Machine Learning Methods ...
Message-ID: <1995Dec19.195032.12210@ptolemy-ethernet.arc.nasa.gov>
Originator: jair-ed@polya.arc.nasa.gov
Lines: 40
Sender: usenet@ptolemy-ethernet.arc.nasa.gov (usenet@ptolemy.arc.nasa.gov)
Nntp-Posting-Host: polya.arc.nasa.gov
Organization: NASA/ARC Computational Sciences Division
Date: Tue, 19 Dec 1995 19:50:32 GMT
Approved: jair-ed@ptolemy.arc.nasa.gov

JAIR is pleased to announce the publication of the following article:

Weiss, S.M. and Indurkhya, N. (1995)
  "Rule-based Machine Learning Methods for Functional Prediction", 
   Volume 3, pages 383-403.
   PostScript: volume3/weiss95a.ps (527K)
	       compressed, volume3/weiss95a.ps.Z (166K)


   Abstract: We describe a machine learning method for predicting the
   value of a real-valued function, given the values of multiple input
   variables. The method induces solutions from samples in the form of
   ordered disjunctive normal form (DNF) decision rules. A central
   objective of the method and representation is the induction of
   compact, easily interpretable solutions.  This rule-based decision
   model can be extended to search efficiently for similar cases prior to
   approximating function values. Experimental results on real-world data
   demonstrate that the new techniques are competitive with existing
   machine learning and statistical methods and can sometimes yield
   superior regression performance.

The PostScript file is available via:
   
 -- comp.ai.jair.papers

 -- World Wide Web: The URL for our World Wide Web server is
       http://www.cs.washington.edu/research/jair/home.html

 -- Anonymous FTP from either of the two sites below:
      CMU:   p.gp.cs.cmu.edu        directory: /usr/jair/pub/volume3
      Genoa: ftp.mrg.dist.unige.it  directory:  pub/jair/pub/volume3

 -- automated email. Send mail to jair@cs.cmu.edu or jair@ftp.mrg.dist.unige.it
    with the subject AUTORESPOND, and the body GET VOLUME3/FILE-NM
    (e.g., GET VOLUME3/MOONEY95A.PS)
    Note: Your mailer might find our files too large to handle. Also, note  
    that compressed files cannot be emailed, since they are binary files.

 -- JAIR Gopher server: At p.gp.cs.cmu.edu, port 70. 

For more information about JAIR, check out our WWW or FTP sites, or
send electronic mail to jair@cs.cmu.edu with the subject AUTORESPOND
and the message body HELP, or contact jair-ed@ptolemy.arc.nasa.gov.



