Title:	EXTRACTION OF CLASSIFICATION MODELS USING A BEE SWARM APPROACH
Author(s):	Sadjia Benkhider and Mohamed Badache
ISBN:	978-989-8533-80-7
Editors:	Ajith P. Abraham, Jörg Roth and Guo Chao Peng
Year:	2018
Edition:	Single
Keywords:	Data Mining, Supervised Classification, Rules, Michigan Optimisation, Bee Swarm
Type:	Short Paper
First Page:	209
Last Page:	213
Language:	English
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Full Contents:	click to dowload
Paper Abstract:	This paper provides a metaheuristic-based of classification rules. Indeed, The classification problem is a data mining task which belongs to the NP-Complete problem class. This is a combinatorial problem which may find good solutions using metaheuristics approaches. We are interested in adapting the Bee Swarm Optimisation (BSO) algorithm which is relatively a new metaheuristic. Our aim is to discover a classification model. This BSO approach already gave some interesting solutions for the well-known SAT problem and we will show the efficiency of the method for the Problem of the Extraction of Classification Rules also.
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