Dimension reduction for outlier detection using DOBIN

Sevvandi Kandanaarachchi, Rob J. Hyndman

Research output: Contribution to journalArticleResearchpeer-review

Abstract

This article introduces DOBIN, a new approach to select a set of basis vectors tailored for outlier detection. DOBIN has a simple mathematical foundation and can be used as a dimension reduction tool for outlier detection tasks. We demonstrate the effectiveness of DOBIN on an extensive data repository, by comparing the performance of outlier detection methods using DOBIN and other bases. We further illustrate the utility of DOBIN as an outlier visualization tool. The R package dobin implements this basis construction. Supplementary materials for this article are available online.

Original languageEnglish
Pages (from-to)204-219
Number of pages16
JournalJournal of Computational and Graphical Statistics
Volume31
Issue number1
DOIs
Publication statusPublished - 2021

Keywords

  • Basis vectors
  • Dimension reduction
  • Outlier detection
  • Outlier visualization

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