Skip to main content

A genetic algorithm for generalized rule induction

Freitas, Alex A. (1999) A genetic algorithm for generalized rule induction. In: Roy, Rajkumar and Furuhashi, Takeshi and Chawdhry, Pravir K., eds. Advances in Soft Computing Engineering Design and Manufacturing. Springer, London, UK, pp. 340-353. ISBN 1-85233-062-7. (doi:10.1007/978-1-4471-0819-1_25) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:21710)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1007/978-1-4471-0819-1_25

Abstract

Data mining consists of the efficient discovery of knowledge from databases. This paper presents a new genetic algorithm designed for discovering a few interesting, high-level prediction rules from databases, rather than discovering classification knowledge (often a large rule set) as usual in the literature. Three important data mining issues addressed by our algorithm are the interestingness of the discovered knowledge, the computational efficiency of the algorithm, and the trade-off between representation expressiveness and efficiency.

Item Type: Book section
DOI/Identification number: 10.1007/978-1-4471-0819-1_25
Uncontrolled keywords: genetic algorithms; data mining; knowledge discovery; generalized rule induction
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Mark Wheadon
Date Deposited: 02 Sep 2009 11:26 UTC
Last Modified: 16 Feb 2021 12:32 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/21710 (The current URI for this page, for reference purposes)
Freitas, Alex A.: https://orcid.org/0000-0001-9825-4700
  • Depositors only (login required):