Interval valued fuzzy sets based on normal forms
Fuzzy Sets and Systems
On the multistage Bayes classifier
Pattern Recognition
Arbitrarily Tight Upper and Lower Bounds on the Bayesian Probability of Error
IEEE Transactions on Pattern Analysis and Machine Intelligence
Lower Bounds for Bayes Error Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Intuitionistic Fuzzy Sets in Intelligent Data Analysis for Medical Diagnosis
ICCS '01 Proceedings of the International Conference on Computational Science-Part II
On the Dengfeng-Chuntian similarity measure and its application to pattern recognition
Pattern Recognition Letters
Combining Pattern Classifiers: Methods and Algorithms
Combining Pattern Classifiers: Methods and Algorithms
On the cardinalities of interval-valued fuzzy sets
Fuzzy Sets and Systems
On the Mean Accuracy of Hierarchical Classifiers
IEEE Transactions on Computers
Similarity Measure of Interval-Valued Fuzzy Sets and Application to Pattern Recognition
FSKD '08 Proceedings of the 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 01
On the Mitchell similarity measure and its application to pattern recognition
Pattern Recognition Letters
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The paper considers the problem of pattern recognition based on Bayes rule. In this model of classification, we use interval-valued fuzzy observations. The paper focuses on the probability of error on certain assumptions. A probability of misclassifications is derived for a classifier under the assumption that the features are class-conditionally statistically independent, and we have interval-valued fuzzy information on object features instead of exact information. Additionally, a probability of the interval-valued fuzzy event is represented by the real number as upper and lower probability. Numerical example concludes the work.