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Patterns Based Classifiers

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Abstract

Data mining is one of the most important areas in the 21 century for its applications are wide ranging. This includes medicine, finance, commerce and engineering, to name a few. Pattern mining is amongst the most important and challenging techniques employed in data mining. Patterns are collections of items which satisfy certain properties. Emerging Patterns are those whose frequencies change significantly from one dataset to another. They represent strong contrast knowledge and have been shown very successful for constructing accurate and robust classifiers. In this paper, we examine various kinds of patterns. We also investigate efficient pattern mining techniques and discuss how to exploit patterns to construct effective classifiers.

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Authors and Affiliations

  1. The Department of Computer Science and Software Engineering, The University of Melbourne, Melbourne, Australia

    Kotagiri Ramamohanarao & Hongjian Fan

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  1. Kotagiri Ramamohanarao
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  2. Hongjian Fan
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Correspondence to Hongjian Fan.

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Ramamohanarao, K., Fan, H. Patterns Based Classifiers. World Wide Web 10, 71–83 (2007). https://doi.org/10.1007/s11280-006-0012-7

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