Knowledge-based learning integrating acquisition and learning
- 1 January 1990
- proceedings article
- Published by Association for Computing Machinery (ACM)
- Vol. 2, 932-941
- https://doi.org/10.1145/98894.99102
Abstract
Empirical learning algorithms are hampered by their inability to use domain knowledge to guide the induction of new rules. This paper describes knowledge-based learning, an approach to learning that selects the examples and relevant attributes for an empirical algorithm. Knowledge-based learning can be used for developing rules for engineering expert systems. Engineers often have some rules for problem solving, but also many experiences (examples) that facilitate solving problems. Knowledge-based learning systems are able to use both forms of knowledge.This publication has 0 references indexed in Scilit: