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An Extended Fuzzy-kNN Approach to Solving Class-imbalanced Problems
Zhigang Xiong, Junzo Watada, Zhenyuan Xu, Bo Wang, Shing Chiang Tan
200 - 209
10.3233/978-1-61499-405-3-200
Frontiers in Artificial Intelligence and Applications
Volume 262: Smart Digital Futures 2014
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.

$35.00 / €27.50 / £22.00
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