A Partition of Feature Space Based on Information Energy in Classification with Fuzzy Observations
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The paper considers the partition problem of feature space in classification. The partition is based on information energy for fuzzy events. In this paper we use Bayes rule for classification with fuzzy observations and exact classes. Additionally a probability of misclassifications is derived for fuzzy information on object features. The results show deterioration the quality of classification when we use fuzzy information on object features instead of exact information and are compared with the partition of feature space. Numerical example concludes the work.
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