Interval-Valued Fuzzy Observations in Bayes Classifier
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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.
KeywordsBayes rule probability of error interval-valued fuzzy observations
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