Share Email Print

Proceedings Paper

Pipelining machine learning algorithms for knowledge discovery
Author(s): Allan L. Egbert Jr.; Robert Chris Lacher
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

A rule-generating algorithm, Incremental Reduced Error Pruning (IREP), has been proposed by Furnkranz and Widmer. A modified IREP algorithm (RIPPERk) may be applied to raw data representing a classification problem. Introduced by Cohen, 1995, RIPPERk generates a set of hypotheses in the form of if-then rules. The resulting solution maybe coarse or compete, covering all outlyers in the classification data set.

Paper Details

Date Published: 30 March 2000
PDF: 6 pages
Proc. SPIE 4055, Applications and Science of Computational Intelligence III, (30 March 2000); doi: 10.1117/12.380565
Show Author Affiliations
Allan L. Egbert Jr., Florida State Univ. (United States)
Robert Chris Lacher, Florida State Univ. (United States)

Published in SPIE Proceedings Vol. 4055:
Applications and Science of Computational Intelligence III
Kevin L. Priddy; Paul E. Keller; David B. Fogel, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?