Efficient mining of jumping emerging patterns with occurrence counts for classification

Authors:
Łukasz Kobyliński;Krzysztof Walczak
Affiliations:
Institute of Computer Science, Warsaw University of Technology, Warszawa, Poland;Institute of Computer Science, Warsaw University of Technology, Warszawa, Poland
Venue:
Transactions on rough sets XIII
Year:
2011

Citing 15
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Abstract

In this paper we propose an efficient method of discovering Jumping Emerging Patterns with Occurrence Counts for the use in classification of data with numeric or nominal attributes. This new extension of Jumping Emerging Patterns proved to perform well when classifying image data and here we experimentally compare it to other methods, by using generalized border-based pattern mining algorithm to build the classifier.