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XML for Data Warehousing Chances and Challenges Read chapter Read first chapter

2003 | OriginalPaper | Chapter

On Complementarity of Cluster and Outlier Detection Schemes

Authors : Zhixiang Chen, Ada Wai-Chee Fu, Jian Tang

Published in: Data Warehousing and Knowledge Discovery

Publisher: Springer Berlin Heidelberg

Included in: Professional Book Archive

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We are interested in the problem of outlier detection, which is the discovery of data that deviate a lot from other data patterns. Hawkins [7] characterizes an outlier in a quite intuitive way as follows: An outlier is an observation that deviates so much from other observations as to arouse suspicion that it was generated by a different mechanism.

previous chapter Incremental OPTICS: Efficient Computation of Updates in a Hierarchical Cluster Ordering
next chapter Cluster Validity Using Support Vector Machines
Metadata
Title
On Complementarity of Cluster and Outlier Detection Schemes
Authors
Zhixiang Chen
Ada Wai-Chee Fu
Jian Tang
Copyright Year
2003
Publisher
Springer Berlin Heidelberg
Book
Data Warehousing and Knowledge Discovery

Print ISBN: 978-3-540-40807-9

Electronic ISBN: 978-3-540-45228-7

Copyright Year: 2003

DOI
https://doi.org/10.1007/978-3-540-45228-7_24

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