One-class classifier based on extreme value statistics
نویسندگان
چکیده
Interest in One-Class Classification methods has soared in recent years due to its wide applicability in many practical problems where classification in the absence of counterexamples is needed. In this paper, a new one class classification rule based on order statistics is presented. It only relies on the embedding of the classification problem into a metric space, so it is suitable for Euclidean or other structured mappings. The suitability of the proposed method is assessed through a comparison both for artificial and real life data sets. The good results obtained pave the road to its application on practical novelty detection problems.
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