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.
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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