Ant-based Feature Decomposition Method in Constructing NMC and NBC ensembles
||International Journal of Computer Trends and Technology (IJCTT)||
|© 2015 by IJCTT Journal|
|Year of Publication : 2015|
|Authors : Abdullah|
|DOI : 10.14445/22312803/IJCTT-V30P108|
Abdullah "Ant-based Feature Decomposition Method in Constructing NMC and NBC ensembles". International Journal of Computer Trends and Technology (IJCTT) V30(1):46-49, December 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Several approaches have been proposed to construct a set of diverse classifiers within an ensemble. One of the approaches is the input features manipulation. Feature decomposition methods are those that manipulate the input feature set in creating the ensemble. However, it is difficult to determine how to partition the feature set into several feature subsets to train base classifiers which may lead to an accurate and diverse ensemble. This paper proposes ant-based feature decomposition method in constructing nearest mean classifier (NMC) ensembles and naïve bayes classifier (NBC) ensembles. Experiments were carried out on several University California, Irvine (UCI) datasets to test the performance of the proposed method. Experimental results showed that the proposed method has successfully constructed better nearest mean classifier (NMC) and naïve bayes classifier (NBC) ensembles.
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Feature decomposition, classifier ensemble, ant-system algorithm.