Probability Error in Bayes Optimal Classifier with Intuitionistic Fuzzy Observations

被引：0
|
作者：
Burduk, Robert [1 ]
机构：
[1] Wroclaw Univ Technol, Chair Systs & Comp Networks, PL-50370 Wroclaw, Poland
来源：
IMAGE ANALYSIS AND RECOGNITION, PROCEEDINGS | 2009年 / 5627卷
关键词：
DECISION-MAKING; LOWER BOUNDS; INFORMATION; SETS; EVENTS;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The paper considers the problem of classification error in pattern recognition. This model of classification is primarily based oil the Bayes rule and secondarily on the notion of intuitionistic fuzzy sets. A probability of misclassifications is derived for a classifier under the assumption that the features are class-conditionally statistically independent, and we have intuitionistic fuzzy information on object features instead of exact information. Additionally, a probability of the intuitionistic fuzzy event is represented by the real number. Numerical example concludes the work.
引用
收藏
页码：359 / 368
页数：10
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