Title
Imbalanced TSK Fuzzy Classifier by Cross-Class Bayesian Fuzzy Clustering and Imbalance Learning.
Abstract
In this paper, a novel construction algorithm called imbalanced Takagi-Sugeno-Kang fuzzy classifier (IB-TSK-FC) for the TSK fuzzy classifier is presented to improve the classification performance and rule-based interpretability for imbalanced datasets. IB-TSK-FC consists of two components: 1) a cross-class Bayesian fuzzy clustering algorithm (BF3C) and 2) an imbalance learning algorithm. In order to achieve high interpretability, BF3C is developed to determine an appropriate number of fuzzy rules and identify antecedent parameters of fuzzy rules from the perspective of the probabilistic model. In addition to inheriting the distinctive advantage of Bayesian fuzzy clustering that the number of clusters can be estimated in the framework of Bayesian inference, BF3C considers repulsion forces between cluster centers belonging to different classes, and uses an alternating iterative strategy to obtain more interpretable antecedent parameters for imbalanced datasets. In order to improve the classification performance for imbalanced datasets, an imbalance learning algorithm is derived to estimate consequent parameters of fuzzy rules on the basis of the weighted average misclassification error. Comprehensive experiments on synthetic and UCI datasets demonstrate the effectiveness of the proposed IB-TSK-FC algorithm.
Year
DOI
Venue
2017
10.1109/TSMC.2016.2598270
IEEE Trans. Systems, Man, and Cybernetics: Systems
Keywords
Field
DocType
Clustering algorithms,Bayes methods,Fuzzy systems,Classification algorithms,Cybernetics,Inference algorithms,Fuzzy sets
Fuzzy clustering,Neuro-fuzzy,Pattern recognition,Fuzzy classification,Defuzzification,Computer science,Fuzzy set operations,Fuzzy logic,Fuzzy set,Artificial intelligence,Adaptive neuro fuzzy inference system,Machine learning
Journal
Volume
Issue
ISSN
47
8
2168-2216
Citations 
PageRank 
References 
16
0.58
38
Authors
4
Name
Order
Citations
PageRank
Xiaoqing Gu1449.30
Fu Lai Chung2153486.72
Hisao Ishibuchi37385503.41
Shitong Wang41485109.13