A New Approach to Classification by Means of Jumping Emerging Patterns

Aleksey Buzmakov 1 Sergei O. Kuznetsov 2 Amedeo Napoli 1
1 ORPAILLEUR - Knowledge representation, reasonning
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : Classification is one of the important fields in data analysis. Generating concept-based (JSM) hypotheses is a well-known approach to this task. Although the accuracy of this approach is quite good, the coverage is often insufficient. In this paper a new classification approach is presented. The approach is based on the similarity of an object to be classified to the current set of hypotheses: it attributes the new object to the class that minimizes the set of new hypotheses when a new object is added to the training set. The proposed approach provides a better coverage in comparison with the classical approach.
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Aleksey Buzmakov, Sergei O. Kuznetsov, Amedeo Napoli. A New Approach to Classification by Means of Jumping Emerging Patterns. FCA4AI: International Workshop "What can FCA do for Artificial Intelligence?" - 2012, Dec 2012, Montpellier, France. ⟨hal-00761602⟩

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