Extraction of crisp logical rules using constructive constrained backpropagation networks

IEEE International Conference on Neural Networks - Conference Proceedings

Volumn 4, Issue , 1997, Pages 2384-2389

  Duch, Wlodzis ^a   Adamczak, Rafal ^a   Grabczewski, Krzysztof ^a  

^a NICOLAUS COPERNICUS UNIVERSITY   (Poland)

Author keywords

[No Author keywords available]

Indexed keywords

BACKPROPAGATION NETWORK; CONSTRUCTIVE ALGORITHMS; IRIS CLASSIFICATIONS; LOGICAL FUNCTIONS; MORE-SPECIFIC RULES; MUSHROOM PROBLEMS; REGULARIZATION TERMS; SMOOTH TRANSFORMATION;

EXTRACTION; NEURAL NETWORKS; BACKPROPAGATION; CONSTRAINT THEORY; KNOWLEDGE ACQUISITION; KNOWLEDGE BASED SYSTEMS; LEARNING SYSTEMS; PROBLEM SOLVING;

ALGORITHMS; NEURAL NETWORKS;

LOGICAL RULE EXTRACTION;

EID: 0030718393     PISSN: 10987576     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICNN.1997.614440     Document Type: Conference Paper

References (10)

1. R. Andrews, J. Diederich, A. B. Tickle. A Survey and Critique of Techniques for Extracting Rules from Trained Artificial Neural Networks, Knowledge-Based Systems 8: 373-389, 1995
2. S. M. Weiss, I. Kapouleas. An empirical comparison of pattern recognition, neural nets and machine learning classification methods, in: J. W. Shavlik and T. G. Dietterich, Readings in Machine Learning, Morgan Kauffman Publ, CA 1990
3. M. W. Craven, J. W. Shavlik. Extracting Tree-Structured Representations of Trained Networks, Adv. in Neural Info. Processing 8: 2430, 1996
4. W. Duch, G. H. F. Diercksen. Feature Space Mapping as a universal adaptive system, Computer Physics Communications, 87: 341-371, 1995
5. W. Duch and N. Jankowski, Bi-radial transfer functions, in Proc. second conference on neural networks and their applications, Orle Gniazdo, Poland, vol. I, pp. 131-137, 1996.
6. W. Duch, R. Adamczak, K. Grabczewski, Constrained backpropagation for feature selection and extraction of logical rules, in: Proc. of "Colloquiua in AI", Lodz, Poland 1996, p. 163-170
7. J. M. Zurada. Introduction to Artificial Neural Systems, West Publishing Company, St Paul, 1992.
8. D. J. MacKay.-4 practical Bayesian framework for backpropagation networks, Neural Computations 4: 448-472, 1992
9. C. J. Mertz, P. M. Murphy, UCI repository of machine learning databases
10. M. Ishikawa, Rule extraction by succesive reg-ularization, in: Proc. of the 1996 IEEE ICNN, Washington, June 1996, pp. 1139-1143.