An extended fuzzy-kNN approach to solving class-imbalanced problems


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

Full text not available from this repository.


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


Downloads per month over past year

View ItemEdit (login required)