The search for novel and useful patterns within large databases, known as data mining, has become of great importance owing to the ever-increasing amounts of data collected by large organizations. In particular, the emphasis is on heuristic search methods which are able to discover patterns that are hard or impossible to detect using standard query mechanisms and classical statistical techniques. In this paper, an evolutionary system that is capable of extracting explicit classification rules is presented. The results are compared with those obtained by other approaches

An evolutionary system for automatic explicit rule extraction

DE FALCO I;IAZZETTA A;TARANTINO E
2000

Abstract

The search for novel and useful patterns within large databases, known as data mining, has become of great importance owing to the ever-increasing amounts of data collected by large organizations. In particular, the emphasis is on heuristic search methods which are able to discover patterns that are hard or impossible to detect using standard query mechanisms and classical statistical techniques. In this paper, an evolutionary system that is capable of extracting explicit classification rules is presented. The results are compared with those obtained by other approaches
2000
Inglese
Proceeding of IEEE Congress on Evolutionary Computation (CEC2000)
IEEE Congress on Evolutionary Computation (CEC2000)
450
457
8
0-7803-6375-2
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=870331
IEEE Computer Society Press
Loa Alamitos [CA]
STATI UNITI D'AMERICA
Sì, ma tipo non specificato
July 16- 19,2000
La Jolla, California, USA
4
none
DE FALCO, I; DELLA CIOPPA, A; Iazzetta, A; Tarantino, E
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/215651
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