CMU Artificial Intelligence Repository
ML-Progs: More "Research-Level" Implementations of Learning
Algorithms
areas/learning/systems/utexas/progs/
This directory contains a copy of more "research-level" versions of
the inductive classification algorithms and software for automated
experiments that generate learning curves that compare several systems.
Programs include:
1. AQ
2. Bayes independent classification system.
3. COBWEB
4. DEDUCE
5. Extentron
6. FOIL (First Order Inductive Learning) in Lisp and Prolog
7. ID3
8. K-Nearest Neighbor Algorithm
9. Perceptron
10. Backprop
11. A dual propositional version of FOIL for learning CNF.
12. A propositional version of FOIL for learning DNF.
13. Functions for running statistical t-test on results of experiments.
Origin:
cs.utexas.edu:/pub/mooney/ml-progs/
Requires: Common Lisp, Prolog
Copying: Copyright (c) 1991 by Raymond J. Mooney
Use permitted for educational and research purposes only.
Users are requested, but not required, to inform Raymond
J. Mooney of any noteworthy uses of this software.
Please see the file readme.txt for details.
CD-ROM: Prime Time Freeware for AI, Issue 1-1
Author(s): Raymond J. Mooney, Jude W. Shavlik, Paul Baffes, John Zelle
Contact: Raymond J. Mooney
Assistant Professor
Department of Computer Sciences
University of Texas at Austin
Keywords:
AQ, Authors!Baffes, Authors!Mooney, Authors!Zelle,
Backpropagation, Bayes Classification, CNF!FOIL, COBWEB,
DEDUCE, DNF!FOIL, Extentron, FOIL, ID3,
Inductive Classification, K Nearest Neighbor, Lisp!Code,
Machine Learning, Perceptrons, Prolog!Code, Statistics,
T-Test, Teaching Materials
References:
Quinlan, J. R., "Learning Logical Definitions from Relations,"
in Machine Learning, 5, 1990.
Last Web update on Mon Feb 13 10:24:36 1995
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