Citation

Tan, Shing Chiang (2014) An extended fuzzy-kNN approach to solving class-imbalanced problems. In: Smart Digital Futures 2014. Frontiers in Artificial Intelligence and Applications, 262 . IOS Press, pp. 200-209. ISBN 978-1-61499-405-3

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Abstract

In this paper, for solving imbalanced classification problem, more attention is placed on data points in the boundary area between two classes. The fuzzy k-nearest neighbors algorithm, which has good performance in conventional classification problems, is adapted here to solve imbalanced classification problems, where G-mean accuracy is used to evaluate our proposal method and compare it with other approaches.

Item Type:	Book Section
Subjects:	T Technology > T Technology (General)
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	21 Jul 2014 08:53
Last Modified:	10 Apr 2015 04:55
URII:	http://shdl.mmu.edu.my/id/eprint/5637

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