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Original Article

JJCIT. 2017; 3(3): 172-185


A Binary Classifier Based On Firefly Algorithm

Raed Al-Abdallah, Ameera Jaradat, Iyad Abu Doush, Yazan Jaradat.

Abstract
This work implements the Firefly algorithm (FA) to find the best decision hyper-plane in the feature space. The proposed classifier uses a cross-validation of a 10-fold portioning for the training and the testing phases used for classification. Five pattern recognition binary benchmark problems with different feature vector dimensions are used to demonstrate the effectiveness of the proposed classifier. We compare the FA classifier results with other approaches through two experiments. The experimental results indicated that FA classifier is a competitive classification technique. The FA shows better results in three out of the four tested datasets used in the second experiment.

Key words: Swarm-based algorithms, Binary classification problems, Firefly algorithms


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The articles in Bibliomed are open access articles licensed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (https://creativecommons.org/licenses/by-nc-sa/4.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.
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