Freitas, A.A. (1997) A Genetic Programming Framework for Two Data Mining Tasks: Classification and Generalized Rule Induction. In: Genetic Programming 1997: Proc 2nd Annual Conf.
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Abstract
This paper proposes a genetic programming (GP) framework for two major data mining tasks, namely classification and generalized rule induction. The framework emphasizes the integration between a GP algorithm and relational database systems. In particular, the fitness of individuals is computed by submitting SQL queries to a (parallel) database server. Some advantages of this integration from a data mining viewpoint are scalability, data-privacy control and automatic parallelization.
| Item Type: | Conference or workshop item (Paper) |
|---|---|
| Subjects: | Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, |
| Divisions: | Faculties > Science Technology and Medical Studies > School of Computing > Applied and Interdisciplinary Informatics Group |
| Depositing User: | Mark Wheadon |
| Date Deposited: | 29 Jul 2009 17:52 |
| Last Modified: | 28 May 2012 15:00 |
| Resource URI: | http://kar.kent.ac.uk/id/eprint/21483 (The current URI for this page, for reference purposes) |
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