CMU Artificial Intelligence Repository
ML-Code: Lisp Code for Assignments in Mooney's Machine
This directory contains a copy of the Common Lisp code
corresponding to the assignments for the graduate course in machine
learning taught by Dr. Mooney.
The programs include:
1. AQ algorithms for learning from examples. Uses either beam
search with bounded stars or the version space algorithm to
3. COBWEB. Incremental conceptual clustering algorithm (with
4. DEDUCE. Prolog-like theorem prover or deductive retrieval
system. Uses generators to retrieve one answer at a time and
also generates proofs. Supports only backward chaining, with
optional depth bound on the number of rules.
5. EGGS. Explanation-Based Generalizer. EGGS can generalize the
proofs returned by DEDUCE and generate macro-rules from the
general proofs. These macro-rules are stored and preferentially
used in future deductions to increase performance.
6. EXPLORER. In the spirit of AM, but more limited. Explores a
space of concepts, guided by "interestingness" measures and
makes conjectures about the concepts it explores.
7. ID3 algorithm for learning from examples. Produces decision trees
discriminating positive and negative instances.
8. PERCEPTRON. Simple system for learning from examples
using the perceptron learning procedure to adjust a set of
weights on a single linear threshold unit until all of the
training examples are correctly classified.
9. VERSION-SPACE algorithm for incremental learning from examples.
Requires: Common Lisp
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
Contact: Raymond J. Mooney
Department of Computer Sciences
University of Texas at Austin
AM, AQ, Authors!Mooney, Authors!Shavlik, Backpropagation,
Backward Chaining, COBWEB, Clustering, DEDUCE,
Decision Trees, Deductive Retrieval, EBG, EGGS, EXPLORER,
ID3, Incremental Conceptual Clustering, Incremental Learning,
Inductive Classification, Learning from Examples, Lisp!Code,
Machine Learning, Perceptrons, Teaching Materials,
Theorem Proving, Version Spaces
Last Web update on Mon Feb 13 10:24:34 1995