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Outlier detection

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Abstract

Outlier detection is an area of research with a long history which has applications in many fields. This article provides a nontechnical and concise overview of the commonly used approaches for detecting outliers, including classical methods, new challenges posed by real-world massive data, and some of the key advances made in recent years. © 2011 John Wiley & Sons, Inc. WIREs Data Mining Knowl Discov 2011 1 261–268 DOI: 10.1002/widm.19

This article is categorized under:

  • Algorithmic Development > Scalable Statistical Methods
  • Fundamental Concepts of Data and Knowledge > Motivation and Emergence of Data Mining
  • Technologies > Statistical Fundamentals
  • Technologies > Structure Discovery and Clustering

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