Abstract
The kbann system uses neural networks to refine domain theories. Currently, domain knowledge in kbann is expressed as nonrecursive, propositional rules. We extend kbann to domain theories expressed as finite-state automata. We apply finite-state KBANN to the task of predicting how proteins fold, producing a small but statistically significant gain in accuracy over both a standard neural network approach and a non-learning algorithm from the biological literature. Our method shows promise at solving this and other real-world problems that can be described in terms of statedependent decisions.
Original language | English (US) |
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Title of host publication | Proceedings of the 8th International Workshop on Machine Learning, ICML 1991 |
Editors | Lawrence A. Birnbaum, Gregg C. Collins |
Publisher | Morgan Kaufmann Publishers, Inc. |
Pages | 524-528 |
Number of pages | 5 |
ISBN (Electronic) | 1558602003, 9781558602007 |
DOIs | |
State | Published - 1991 |
Externally published | Yes |
Event | 8th International Workshop on Machine Learning, ICML 1991 - Evanston, United States Duration: Jun 1 1991 → … |
Publication series
Name | Proceedings of the 8th International Workshop on Machine Learning, ICML 1991 |
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Conference
Conference | 8th International Workshop on Machine Learning, ICML 1991 |
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Country/Territory | United States |
City | Evanston |
Period | 6/1/91 → … |
Bibliographical note
Publisher Copyright:© ICML 1989.All rights reserved