Design And Development Of GP-Based Data Mining Systems

Initially, function using genetic programming (GP) is investigated through symbolic regression for data mining applications. Various kinds of functions are investigated including function learning tasks as well as Boolean functions learning. The objective of the initial investigation is to review ho...

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Main Author: Lim, Amy Hui Lan
Format: Thesis
Published: 2003
Subjects:
Online Access:http://shdl.mmu.edu.my/69/
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author Lim, Amy Hui Lan
author_facet Lim, Amy Hui Lan
author_sort Lim, Amy Hui Lan
building MMU Institutional Repository
collection Online Access
description Initially, function using genetic programming (GP) is investigated through symbolic regression for data mining applications. Various kinds of functions are investigated including function learning tasks as well as Boolean functions learning. The objective of the initial investigation is to review how GP is applied to function learning tasks. The drawbacks of this method are identified. Hybrid GP technique based on genetic algorithm-program (GA-P) for function learning tasks with variables and constants is investigated. This hybrid GP technique is further expanded to new hybrid GA SA-p. The new hybrid GA SA-P combining genetic algorithms (GA) and simulated annealing (SA) is proposed for function learning tasks with numeric constants. The convergence bahaviour will be compared with existing GP and genetic algorithm-program (GP-P). Application of Gp is extended to discover interesting rules among data sets. Given a set of data and appropriate parameter settings, GP is used to discover set of rules that describes the relationships that exist among the data. Finally, GP is investigated as decision tree classifier for classifying binary and multiclass classification problems. The simulation results will be compared with C4.5 decision tree algorithm.
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format Thesis
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institution Multimedia University
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last_indexed 2025-11-14T17:56:23Z
publishDate 2003
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spelling mmu-692009-12-04T11:30:16Z http://shdl.mmu.edu.my/69/ Design And Development Of GP-Based Data Mining Systems Lim, Amy Hui Lan LB2300 Higher Education Initially, function using genetic programming (GP) is investigated through symbolic regression for data mining applications. Various kinds of functions are investigated including function learning tasks as well as Boolean functions learning. The objective of the initial investigation is to review how GP is applied to function learning tasks. The drawbacks of this method are identified. Hybrid GP technique based on genetic algorithm-program (GA-P) for function learning tasks with variables and constants is investigated. This hybrid GP technique is further expanded to new hybrid GA SA-p. The new hybrid GA SA-P combining genetic algorithms (GA) and simulated annealing (SA) is proposed for function learning tasks with numeric constants. The convergence bahaviour will be compared with existing GP and genetic algorithm-program (GP-P). Application of Gp is extended to discover interesting rules among data sets. Given a set of data and appropriate parameter settings, GP is used to discover set of rules that describes the relationships that exist among the data. Finally, GP is investigated as decision tree classifier for classifying binary and multiclass classification problems. The simulation results will be compared with C4.5 decision tree algorithm. 2003 Thesis NonPeerReviewed Lim, Amy Hui Lan (2003) Design And Development Of GP-Based Data Mining Systems. Masters thesis, Multimedia University. http://vlib.mmu.edu.my/diglib/login/dlusr/login.php
spellingShingle LB2300 Higher Education
Lim, Amy Hui Lan
Design And Development Of GP-Based Data Mining Systems
title Design And Development Of GP-Based Data Mining Systems
title_full Design And Development Of GP-Based Data Mining Systems
title_fullStr Design And Development Of GP-Based Data Mining Systems
title_full_unstemmed Design And Development Of GP-Based Data Mining Systems
title_short Design And Development Of GP-Based Data Mining Systems
title_sort design and development of gp-based data mining systems
topic LB2300 Higher Education
url http://shdl.mmu.edu.my/69/
http://shdl.mmu.edu.my/69/