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Constructive Induction of Fuzzy Cartesian Granule Feature Models using Genetic Programming

Jimi Shanahan, James Baldwin, Trevor Martin
The G_DACG (Genetic Discovery of Additive Cartesian Granule feature models) constructive induction algorithm is presented as a means of automatically identifying rule-based Cartesian granule feature models from example data. G_DACG combines the powerful search capabilities of genetic programming with a rather novel and cheap fitness function based upon the semantic separation of learnt concepts expressed in terms of fuzzy sets extracted over Cartesian granule features. G_DACG is illustrated on a variety of artificial and real world problems.
Genetic Programming Track of GECCO 99, Orlando
1999
1999/207

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gecco99.pdf (11.21 kB)