International Journal of Soft Computing

Year: 2011
Volume: 6
Issue: 2
Page No. 20 - 25

An Evolutionary Multi Label Classification Using Associative Rule Mining

Authors : J. Arunadevi and V. Rajamani

Abstract: Multi-label spatial classification based on association rules with Multi Objective Genetic Algorithms (MOGA) is proposed to deal with multiple class labels problem which is hard to settle by existing methods. In this study we adapt problem transformation for the Multi label classification. We use Hybrid evolutionary algorithm for the optimization in the generation of spatial association rules which addresses single label. MOGA is used to combine the single labels into multi labels with the conflicting objectives predictive accuracy and comprehensibility. Finally we built the classifier with a sorting mechanism. The algorithm is executed and the results are compared with Decision trees and Neural network based classifiers, the proposed method out performs the existing.

How to cite this article:

J. Arunadevi and V. Rajamani, 2011. An Evolutionary Multi Label Classification Using Associative Rule Mining. International Journal of Soft Computing, 6: 20-25.

Design and power by Medwell Web Development Team. © Medwell Publishing 2024 All Rights Reserved