An Oriented Clonal Selection Algorithm for Associative Classification

Wan Li Kang; Jing Jing Wu; Du Wu Cui; Li Zhao

doi:10.4028/www.scientific.net/AMM.170-173.3320

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 170-173An Oriented Clonal Selection Algorithm for...

An Oriented Clonal Selection Algorithm for Associative Classification

Abstract:

In this paper, we present an oriented clonal selection algorithm (O-CLONALG) for mining association rules effectively for classification. Different with the traditional evolutionary algorithms, O-CLONALG firstly scans dataset one time to find the frequent rules with one item. The items are used to generate new rules and the mutation operation is limited in it. When mutation operation takes place, each rule in the same generation was added a new item. The results have shown that it is efficient in dealing with the problem on the complexity of the rule search space. At the same time, good classification accuracy has been achieved

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Periodical:

Applied Mechanics and Materials (Volumes 170-173)

Pages:

3320-3323

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.170-173.3320

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Online since:

May 2012

Authors:

Wan Li Kang, Jing Jing Wu, Du Wu Cui, Li Zhao

Keywords:

Artificial Immune System, Associative Classification, Clonal Selection Algorithm, Evolutionary Computations

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