Ant-based Feature Decomposition Method in Constructing NMC and NBC ensembles
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International Journal of Computer Trends and Technology (IJCTT) | 
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| © 2015 by IJCTT Journal | ||
| Volume-30 Number-1 |
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| 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.
Abstract -
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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Keywords
Feature decomposition, classifier
ensemble, ant-system algorithm.