Sensitivity analysis of fuzzy rule-based classification systems by means of the Lipschitz condition

被引：1
|
作者：
Mesiarova-Zemankova, Andrea [1 ]
机构：
[1] Slovak Acad Sci, Math Inst, Bratislava 81473, Slovakia
来源：
SOFT COMPUTING | 2016年 / 20卷 / 01期
关键词：
Classification; Supervised learning; Fuzzy reasoning; Accuracy; Multi-polar aggregation; REASONING METHODS; ELICITATION;
D O I：
10.1007/s00500-015-1744-z
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The fuzzy rule-based classifier can be taken as a function that assigns to a point from the feature space a class, or a class with an association degree. Under this assumption, the robustness of fuzzy rule-based classifiers is investigated by means of the Lipschitz condition. The Lipschitz continuity of fuzzy sets, fuzzy rules and whole fuzzy rule-based classifiers is examined for multi-polar outputs, extended multi-polar outputs and outputs in the form of a class. Related performance of a fuzzy rule-based classifier is also discussed. All studied concepts are shown on an exemplar fuzzy rule-based classifier.
引用
收藏
页码：103 / 113
页数：11
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