Improving Induction Decision Trees with Parallel Genetic Programming

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	Similar Articles Articles by G. Folino Articles by C. Pizzuti Articles by G. Spezzano

10th Euromicro Workshop on Parallel, Distributed and Network-based Processing (EUROMICRO-PDP 2002)

Canary Islands, Spain

January 09-January 11

ISBN: 0-7695-1444-8

	ASCII Text	x
	G. Folino, C. Pizzuti, G. Spezzano, "Improving Induction Decision Trees with Parallel Genetic Programming," Parallel, Distributed, and Network-Based Processing, Euromicro Conference on, pp. 0181, 10th Euromicro Workshop on Parallel, Distributed and Network-based Processing (EUROMICRO-PDP 2002), 2002.

	BibTex	x
	@article{ 10.1109/EMPDP.2002.994264, author = {G. Folino and C. Pizzuti and G. Spezzano}, title = {Improving Induction Decision Trees with Parallel Genetic Programming}, journal ={Parallel, Distributed, and Network-Based Processing, Euromicro Conference on}, volume = {0}, year = {2002}, issn = {1066-6192}, pages = {0181}, doi = {http://doi.ieeecomputersociety.org/10.1109/EMPDP.2002.994264}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Parallel, Distributed, and Network-Based Processing, Euromicro Conference on TI - Improving Induction Decision Trees with Parallel Genetic Programming SN - 1066-6192 SP EP A1 - G. Folino, A1 - C. Pizzuti, A1 - G. Spezzano, PY - 2002 KW - Decision Trees KW - Genetic programming KW - classification KW - parallel processing VL - 0 JA - Parallel, Distributed, and Network-Based Processing, Euromicro Conference on ER -

G. Folino, ISI-CNR

C. Pizzuti, ISI-CNR

G. Spezzano, ISI-CNR

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/EMPDP.2002.994264

A parallel genetic programming approach to induce decision trees in large data sets is presented. A population of trees is evolved by employing the genetic operators and every individual is evaluated by using a fitness function based on the J-measure. The method is able to deal with large data sets since it uses a parallel implementation of genetic programming through the grid model. Experiments on data sets from the UCI machine learning repository show better results with respect to C5. Furthermore, performance results show a nearly linear speedup.

Index Terms:

Decision Trees, Genetic programming, classification, parallel processing

Citation:

G. Folino, C. Pizzuti, G. Spezzano, "Improving Induction Decision Trees with Parallel Genetic Programming," pdp, pp.0181, 10th Euromicro Workshop on Parallel, Distributed and Network-based Processing (EUROMICRO-PDP 2002), 2002

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