A Two-Level Approach based on Integration of Bagging and Voting for Outlier Detection

Doğan A., Birant D.

JOURNAL OF DATA AND INFORMATION SCIENCE, vol.5, no.2, pp.111-135, 2020 (ESCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 5 Issue: 2
  • Publication Date: 2020
  • Doi Number: 10.2478/jdis-2020-0014
  • Journal Name: JOURNAL OF DATA AND INFORMATION SCIENCE
  • Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus, Directory of Open Access Journals
  • Page Numbers: pp.111-135
  • Keywords: Outlier detection, Local outlier factor, Ensemble learning, Bagging, Voting, SUBSPACES
  • Dokuz Eylül University Affiliated: Yes

Abstract

Purpose: The main aim of this study is to build a robust novel approach that is able to detect outliers in the datasets accurately. To serve this purpose, a novel approach is introduced to determine the likelihood of an object to be extremely different from the general behavior of the entire dataset.