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Introduction to Supervised Descriptive Pattern Mining

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Supervised Descriptive Pattern Mining

Abstract

This chapter introduces the supervised descriptive pattern mining task to the reader, providing him/her with the concept of patterns as well as presenting a description of the type of patterns usually found in literature. Patterns on advanced data types are also defined, denoting the usefulness of sequential and spatiotemporal patterns, patterns on graphs, high utility patterns, uncertain patterns, along with patterns defined on multiple-instance domains. The utility of the supervised descriptive pattern mining task is analysed and its main subtasks are formally described, including contrast sets, emerging patterns, subgroup discovery, class association rules, exceptional models, among others. Finally, the importance of analysing the computational complexity in the pattern mining field is also considered, examining different ways of reducing this complexity.

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  1. Computer Science, University of Cordoba, Cordoba, Spain

    Sebastián Ventura & José María Luna

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Ventura, S., Luna, J.M. (2018). Introduction to Supervised Descriptive Pattern Mining. In: Supervised Descriptive Pattern Mining. Springer, Cham. https://doi.org/10.1007/978-3-319-98140-6_1

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