Abstract
In this research, we introduce a classification procedure based on rule induction and fuzzy reasoning. The classifier generalizes attribute information to handle uncertainty, which often occurs in real data. To induce fuzzy rules, we define the corresponding fuzzy information system. A transformation of the derived rules into interval type-2 fuzzy rules is provided as well. The fuzzification applied is optimized with respect to the footprint of uncertainty of the corresponding type-2 fuzzy sets. The classification process is related to a Mamdani type fuzzy inference. The method proposed was evaluated by the F-score measure on benchmark data.
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Reference63 articles.
1. Robust Classification
2. Robust Classification of Financial Risk, NIPS 2018 Workshop on Challenges and Opportunities for AI in Financial Services: The Impact of Fairness, Explainability, Accuracy, and Privacy;Sarkar;arXiv,2018
3. Fuzzy sets
4. Type-2 fuzzy sets made simple
5. Type-2 Fuzzy Sets and Systems: How to Learn About Them;Mendel;IEEE Smc Enewsletter,2009
Cited by
14 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献