An innovative application of a constrained-syntax genetic programming system to the problem of predicting survival of patients.

Bojarczuk, Celia C. and Lopes, Heitor S. and Freitas, Alex A. (2003) An innovative application of a constrained-syntax genetic programming system to the problem of predicting survival of patients. In: Ryan, Conor and Keijzer, Maarten and Poli, Riccardo and Soule, Terence and Tsang, Edward and Costa, Ernesto, eds. Lecture Notes In Computer Science. Lecture Notes in Computer Science, 2610. Springer-Verlag pp. 11-21. ISBN 3-540-00971-X. (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)

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Official URL
http://www.cs.kent.ac.uk/pubs/2003/1729

Abstract

This paper proposes a constrained-syntax genetic programming (GP) algorithm-for discovering classification rules in medical data sets. The proposed GP contains several syntactic constraints to be enforced by the system using a disjunctive normal form representation, so that individuals represent valid rule sets that are easy to interpret. The GP is compared with C4.5 in a real-world medical data set. This data set represents a difficult classification problem, and a new preprocessing method was devised for mining the data.

Item Type: Conference or workshop item (UNSPECIFIED)
Additional information: Conference Information: 6th European Conference on Genetic Programming (EuroGP 2003)
Uncontrolled keywords: genetic programming, data mining, classification
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: 24 Nov 2008 18:01
Last Modified: 17 Jun 2014 14:01
Resource URI: https://kar.kent.ac.uk/id/eprint/13992 (The current URI for this page, for reference purposes)
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