Co-evolutionary Rule-Chaining Genetic Programming

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Co-evolutionary Rule-Chaining Genetic Programming
Abstract. A novel Genetic Programming (GP) paradigm called Coevolutionary Rule-Chaining Genetic Programming (CRGP) has been proposed to learn the relationships among attributes represented by a set of classification rules for multi-class problems. It employs backward chaining inference to carry out classification based on the acquired acyclic rule set. Its main advantages are: 1) it can handle more than one class at a time; 2) it avoids cyclic result; 3) unlike Bayesian Network (BN), the CRGP can handle input attributes with continuous values directly; and 4) with the flexibility of GP, CRGP can learn complex relationship. We have demonstrated its better performance on one synthetic and one real-life medical data sets.
Wing-Ho Shum, Kwong-Sak Leung, Man Leung Wong
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Authors Wing-Ho Shum, Kwong-Sak Leung, Man Leung Wong
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