Paper Details: Downloads: 548
Serial Number: P1120535113
Title: Extracting Logical Classication Rules With Gene Expression Programming: Microarray Case Study
Authors: M.H. Marghny and I.E. El-Semman
Abstract: The benets of nding trends in large volumes of data has driven to the development of data mining technology for over a decade. This paper presents an evolutionary approach for data mining based on enhanced version of gene expression programming (GEP). We enhance the original GEP technique by using a logical operators instead of mathematical ones to represent the chromosome validity evaluation, which results in unconstrained search of the genome space while still ensuring validity of the program's output, it has been demonstrated that GEP greatly surpasses the traditional tree-based GP for its simplicity, high eciency, solution compactness and comprehensibility.
Keywords: Data mining, classication rules, gene expression programming, microarray
Journal/Conference: ICGST Conference on Artificial Intelligence and Machine Learning, AIML-05
Volume:
Issue:
Submission Date: 8/1/2005 12:00:00 AM
Review Date: 10/1/2005 12:00:00 AM
Publishing Date: 12/19/2005 12:00:00 AM
Article Downloads: 548
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