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2014 | OriginalPaper | Buchkapitel

17. Supervised Pattern Mining and Applications to Classification

verfasst von : Albrecht Zimmermann, Siegfried Nijssen

Erschienen in: Frequent Pattern Mining

Verlag: Springer International Publishing

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Abstract

In this chapter we describe the use of patterns in the analysis of supervised data. We survey the different settings for finding patterns as well as sets of patterns. The pattern mining settings are categorized according to whether they include class labels as attributes in the data or whether they partition the data based on these labels. The pattern set mining settings are categorized along several dimensions, including whether they perform iterative mining or post-processing, operate globally or locally, and whether they use patterns directly or indirectly for prediction.

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Titel: Supervised Pattern Mining and Applications to Classification
verfasst von: Albrecht Zimmermann
Siegfried Nijssen
Verlag: Springer International Publishing
Buch: Frequent Pattern Mining
Print ISBN: 978-3-319-07820-5

Electronic ISBN: 978-3-319-07821-2

Copyright-Jahr: 2014
DOI: https://doi.org/10.1007/978-3-319-07821-2_17

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