Learning Concept Classification Rules using Genetic Algorithms Export

@inproceedings{citeulike:2242745, abstract = {In this paper we explore the use of an adaptive search technique (genetic algorithms) to construct a system GABIL which continually learns and refines concept classification rules from its interaction with the environment. The performance of the system is measured on a set of concept learning problems and compared with the performance of two existing systems: ID5R and C4.5. Preliminary results support that, despite minimal system bias, GABIL is an effective concept learner and is quite...}, author = {De Jong, Kenneth A. and Spears, William M.}, booktitle = {Proceedings of the Twelfth International Conference on Artificial Intelligence IJCAI-91}, citeulike-article-id = {2242745}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.56.5640}, keywords = {classification, concept, genetic-algorithm}, posted-at = {2008-01-17 04:35:23}, priority = {2}, title = {Learning Concept Classification Rules using Genetic Algorithms}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.56.5640}, volume = {2}, year = {1991} }

TY - CONF ID - citeulike:2242745 L3 - citeulike-article-id:2242745 N2 - In this paper we explore the use of an adaptive search technique (genetic algorithms) to construct a system GABIL which continually learns and refines concept classification rules from its interaction with the environment. The performance of the system is measured on a set of concept learning problems and compared with the performance of two existing systems: ID5R and C4.5. Preliminary results support that, despite minimal system bias, GABIL is an effective concept learner and is quite... TI - Learning Concept Classification Rules using Genetic Algorithms VL - 2 T2 - Proceedings of the Twelfth International Conference on Artificial Intelligence IJCAI-91 KW - classification KW - concept KW - genetic-algorithm AU - De Jong, Kenneth AU - Spears, William PY - 1991/// UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.56.5640 ER -