Research Article Open Access

Fast Algorithms for Outlier Detection

Fawaz A.M. Masoud1, Moh'd B. Al- Zoubi1, Imad Salah1 and Ali Al-Dahoud1
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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

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.

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Keywords

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