Thread View: comp.lang.prolog
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Started by Werner Emde
Fri, 08 Jan 1993 09:36
Machine Learning Program Library
Author: Werner Emde
Date: Fri, 08 Jan 1993 09:36
Date: Fri, 08 Jan 1993 09:36
176 lines
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8580 bytes
The Machine-Learning-Program-Library with PROLOG implementations of
basic Machine Learning algorithms has been moved from the ftp-server
of the University of Osnabrueck to the ftp-server of the German
National Research Center for Computer Science (GMD).
The programs are now accessible via ftp from 'ftp.gmd.DE' within the
directory 'gmd/mlt/ML-Program-Library'.
Please, consult the attached README-file of the library for further
details.
% file: gmd/mlt/ML-Program-Library/README:
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This is the Machine Learning Program Library
% of the
% Special Interest Group on Machine Learning (FG 1.1.3)
% of the German Society for Computer Science (GI e.V.)
% 7 January 1993
% Anonymous ftp-Server: ftp.gmd.DE (129.26.8.90)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
Included in this library are several PROLOG implementations of
basic machine learning algorithms. The contents of the repository can
remotely copied to other network sites via ftp from
'ftp.gmd.de'. The login-name is 'anonymous', as password enter your
own e-mail address. To find the program directories with the programs,
some small test data sets and demonstration LOG files enter
cd gmd/mlt/ML-Program-Library
The names and addresses of the authors, references to the origin of
the algorithms, and hints how the programs can be started are usually
included in the program files.
The file LOGFILE lists changes and modifications to the library. This
file should make it easy for you to determine what's new since you
last looked at it.
Notes
-----
1) Software delivery: If you have implemented a basic machine learning
algorithm in PROLOG, which is free of copyrights, please send it to
Thomas Hoppe. Order his software documentation file for more details.
2) Bug detection: The algorithms are more or less tested. Somtimes
bugs may occur as a consequence of the subtil differences of
the different PROLOG dialects (especially built-in predicates).
If you find a 'new feature', which you did not expect, inform
Thomas Hoppe so that others can take benefit from your experience.
3) Copyright: Please note the remarks on the copyright and allowed
modifications made by some program authors at the beginning of
the program files.
4) The files may also be ordered via surface or electronic mail.
People without access to the archive should send a short notice
to Thomas Hoppe using the address given below.
5) We appreciate to draw your attention to the fact that the Knowledge
Acquisition and Machine Learning System MOBAL (2.0) is also accesible
accessible via the same anonymous ftp server. The system, a user
guide and a README file are located in the directory
gmd/mlt/Mobal
(MOBAL has been developed using QUINTUS PROLOG 3.1.1 on a SUN4).
Brief Overview of the Program Library
-------------------------------------
Each sub-directory contains a PROLOG (re-)implementation of a basic
machine learning algorithm, one (or more) test data files, and (in
some cases) a small log file produced by running the program on
the test data set using QUINTUS PROLOG (release 2.4).
README this file
LOGFILE description of last changes and additions
aq1/
aq1.pro reimplementation of Jeffrey M. Becker's AQ-PROLOG (based
on Michalski's AQ) (author: Thomas Hoppe)
aq1_1.pro a simple data set
aq1_2.pro Extensions to aq1_1.pro
arch1/
arch1.pro Winston's incremental learning procedure for
structural descriptions (author: Stefan Wrobel)
arch1_1.pro Winston's example archs
arch1.log Log-file of a sample run
arch2/
arch2.pro a minimal implementation of Winstons's ARCH
(author: Ivan Bratko)
arch2_1.pro a small test set
arch2.log Log-file of a sample run
attdsc/
attdsc.pro Ivan Bratko's algorithm for learning attributional
descriptions
attdsc_1.pro Small example set for learning to recognize objects
from their silhouettes
cobweb/
cobweb.pro a PROLOG implementation of Fisher's COBWEB using
CLASSIT's evaluation function to deal with numeric
attributes (author: Joerg-Uwe Kietz)
cobweb_1.pro a simple data set describing some hotels (numeric and
nominal attributes)
cobweb_2.pro Gennari, Langley, and Fisher's rectangle
classification example (numeric attributes)
cobweb_3.pro Fisher's animal classification example (nominal
attributes)
cobweb_4.pro Gennari, Langley, and Fisher's cell classification
example (numeric attributes)
cobweb.log Log-file of running the program the example data
sets
discr/
discr.pro Brazdil's generation of discriminations from
derivation trees (author: Thomas Hoppe)
discr_1.pro Simple abstract example
discr_2.pro Abstract example generating useful and not
ebg/
ebg.pro Basic algorithms for explanation based generalisa-
tion and partial evaluation based on Kedar-Cabelli
& McCarty's idea. Different kinds of simple PROLOG
meta-interpreters.
ebg_1.pro Suicide example for EBG
ebg_2.pro Safe_to_stack example for EBG
useful descriminants (author: Thomas Hoppe)
id3/
idt.pro ID3.1 Implementation of Quinlan's ID3 algorithm
based on the 'gain-ratio'-measure
(authors: Luis Torgo, Thomas Hoppe)
idt_1.pro simple example data set
idt_2.pro simple example data set
idt_3.pro simple example data set
invers/
invers.pro Implementation of absorption and intra-construction
operators for inverse resolution
(author: Thomas Hoppe)
invers_1.pro example calls
logic/
logic.pro Substitution matching, term generalizations,
generalized subsumption
logic_1.pro Example calls
multagent/
multagent.pro Yiu Cheung HO's implementation of Brazdil's tutoring
setting
teacher.pro Teacher's knowledge base
learner1.pro A correct Learner's knowledge base
learner2.pro An erroneous Learner's knowledge base
calls_1.pro Example calls concerning correct knowledge
calls_2.pro Example calls concerning wrong knowledge
vs/
vs.pro Implementation of Mitchell's version space algorithm
vs_1.pro a simple shape and color taxonomy
vs_1.log Log-file of a sample run
Suggestions and complaints regarding the access to the ftp-library
or the Log-files are welcome any time by Werner Emde.
Additional PROLOG implementations of Machine Learning Algorithms are
welcome by Thomas Hoppe who is responsible for the maintenance of the
program library. Thomas Hoppe has made slight changes to the programs
supplied by the different authors in order to make them independent of
a specific PROLOG dialect (as far as possible).
Thomas Hoppe Dr. Werner Emde
Projektgruppe KIT GMD, FIT.KI
Technische Universitaet Berlin Postfach 13 16
Franklinstr. 28/29 Schloss Birlinghoven
D-1000 Berlin 10 D-W-5205 Sankt Augustin 1
Germany Germany
email: hoppet@cs.tu-berlin.de email: werner.emde@gmd.de
Phone: +49.30.314-25494 Phone: +49.2241.14-2282
FAX: +49.30.314-24929 FAX: +49.2241.14-2072
Re: Machine Learning Program Library
Author: Matthew Huntbach
Date: Fri, 08 Jan 1993 11:32
Date: Fri, 08 Jan 1993 11:32
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In article <emde.726485815@hercules> emde@hercules.gmd.de (Werner Emde) writes: >Additional PROLOG implementations of Machine Learning Algorithms are >welcome by Thomas Hoppe who is responsible for the maintenance of the >program library. Thomas Hoppe has made slight changes to the programs >supplied by the different authors in order to make them independent of >a specific PROLOG dialect (as far as possible). > You ought to have Shapiro's model inference system. I am not sure if the code is available anywhere, but the text is given as an appendix to his thesis "Algorithmic Program Debugging" which is published in MIT's Distinguished Dissertation series. I wrote an improved version of it, but I used the Poplog system, mixing Pop-11 with the Prolog, so it wouldn't be translatable. Matthew Huntbach
Re: Machine Learning Program Library
Author: Thomas Hoppe
Date: Fri, 08 Jan 1993 12:19
Date: Fri, 08 Jan 1993 12:19
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mmh@dcs.qmw.ac.uk (Matthew Huntbach) writes: >You ought to have Shapiro's model inference system. I am not >sure if the code is available anywhere, but the text is given >as an appendix to his thesis "Algorithmic Program Debugging" >which is published in MIT's Distinguished Dissertation series. >I wrote an improved version of it, but I used the Poplog >system, mixing Pop-11 with the Prolog, so it wouldn't be >translatable. > >Matthew Huntbach Yes, that's right. Actually I have re-implemented it already some years ago and it is still on my stack of programs "to be included in the lib". Since the behavior of the re-implementation differs from the behavior published in Shapiro's book and since I have compared the code over and over again, it seems that the behavior difference is a result of different Prolog dialects. Thus and because of a lack of time this program isn't yet in the Lib. Anyway, if I find some time in the future it will surely be included. If somebody is interested in it, s/he can mail me directly to get it. Thomas Hoppe -- Thomas Hoppe Projekt KIT-BACK email: hoppet@cs.tu-berlin.de Technische Universitaet Berlin phone: 030-314-25494 Franklinstr. 28/29 fax : 030-314-24929 1000 Berlin 10 Germany priv.: 030-3236564
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