Fuzzy Classifiers with a Two-Stage Reject Option

Yusuke Nojima1; Koyo Kawano2; Hajime Shimahara3; Eric Vernon1; Naoki Masuyama1; Hisao Ishibuchi4

10.1109/FUZZ52849.2023.10309729

2023

IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

1544-5615

979-8-3503-3229-2

2023 IEEE International Conference on Fuzzy Systems (FUZZ)

1-6

13-17 Aug. 2023

Incheon, Korea, Republic of

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

In general, fuzzy classifiers have high interpretability. They can linguistically explain the reason why an input pattern is classified as a particular class through the linguistic interpretation of each antecedent fuzzy set. A reject option that rejects patterns near the boundaries between different classes is an approach to increase the reliability of classifiers. However, the conventional threshold-based reject option may reject more patterns than necessary to achieve high reliability. In this paper, we propose a two-stage reject option where a machine learning model is used after the threshold-based decision by a fuzzy classifier. If the class labels predicted by the machine learning model and the fuzzy classifier are the same, the fuzzy classifier outputs the predicted class label without rejection. Through computational experiments, we discuss the trade-off relation between the accuracy and rejection rate by the proposed two-stage reject option using various machine learning models.

Fuzzy classifiers genetics-based machine learning reject options

其他

英语

EI ; CPCI-S

Japan Society for the Promotion of Science (JSPS) KAKENHI[19K12159]

Computer Science

Computer Science, Artificial Intelligence

WOS:001103277400057

20234915152328

Economic and social effects ; Fuzzy sets ; Machine learning

Artificial Intelligence:723.4 ; Social Sciences:971

IEEE

1.Graduate School of Informatics, Osaka Metropolitan University, Sakai, Japan
2.Graduate School of Engineering, Osaka Prefecture University, Sakai, Japan
3.Collage of Engineering, Osaka Prefecture University, Sakai, Japan
4.Southern University of Science and Technology, Shenzhen, China

Yusuke Nojima,Koyo Kawano,Hajime Shimahara,et al. Fuzzy Classifiers with a Two-Stage Reject Option[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2023:1-6.