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ISSN: 1549-3636 (Print)
ISSN: 1552-6607 (Online)
Research Article Open Access

Fast Algorithms for Outlier Detection

Fawaz A.M. Masoud, Moh'd B. Al- Zoubi, Imad Salah and Ali Al-Dahoud

Abstract

Finding fast algorithms to detect outliers (as unusual objects) by their distance to neighboring objects is a big desire. Two algorithms were proposed to detect outliers quickly. The first was based on the Partial Distance (PD) algorithm and the second was an improved version of the PD algorithm. It was found that the proposed algorithms reduced the number of distance calculations compared to the nested-loop method.

Journal of Computer Science
Volume 4 No. 2, 2008, 129-132

DOI: https://doi.org/10.3844/jcssp.2008.129.132

Submitted On: 18 January 2008 Published On: 28 February 2008

How to Cite: Masoud, F. A., Al- Zoubi, M. B., Salah, I. & Al-Dahoud, A. (2008). Fast Algorithms for Outlier Detection. Journal of Computer Science, 4(2), 129-132. https://doi.org/10.3844/jcssp.2008.129.132

Open AccessCopyright: © 2008 Fawaz A.M. Masoud, Moh'd B. Al- Zoubi, Imad Salah and Ali Al-Dahoud. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Keywords

  • Outlier detection
  • K-Nearest Neighbour (KNN)
  • partial distance
  • data mining