Stream classification with recurring and novel class detection using class-based ensemble

Tahseen Al-Khateeb, Mohammad M. Masud, Latifur Khan, Charu Aggarwal, Jiawei Han, Bhavani Thuraisingham

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Concept-evolution has recently received a lot of attention in the context of mining data streams. Concept-evolution occurs when a new class evolves in the stream. Although many recent studies address this issue, most of them do not consider the scenario of recurring classes in the stream. A class is called recurring if it appears in the stream, disappears for a while, and then reappears again. Existing data stream classification techniques either misclassify the recurring class instances as another class, or falsely identify the recurring classes as novel. This increases the prediction error of the classifiers, and in some cases causes unnecessary waste in memory and computational resources. In this paper we address the recurring class issue by proposing a novel "class-based" ensemble technique, which substitutes the traditional "chunkbased" ensemble approaches and correctly distinguishes between a recurring class and a novel one. We analytically and experimentally confirm the superiority of our method over state-of-the-art techniques.

Original languageEnglish (US)
Title of host publicationProceedings - 12th IEEE International Conference on Data Mining, ICDM 2012
Pages31-40
Number of pages10
DOIs
StatePublished - Dec 1 2012
Event12th IEEE International Conference on Data Mining, ICDM 2012 - Brussels, Belgium
Duration: Dec 10 2012Dec 13 2012

Publication series

NameProceedings - IEEE International Conference on Data Mining, ICDM
ISSN (Print)1550-4786

Other

Other12th IEEE International Conference on Data Mining, ICDM 2012
CountryBelgium
CityBrussels
Period12/10/1212/13/12

Keywords

  • Novel class
  • Recurring class
  • Stream classification

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Al-Khateeb, T., Masud, M. M., Khan, L., Aggarwal, C., Han, J., & Thuraisingham, B. (2012). Stream classification with recurring and novel class detection using class-based ensemble. In Proceedings - 12th IEEE International Conference on Data Mining, ICDM 2012 (pp. 31-40). [6413716] (Proceedings - IEEE International Conference on Data Mining, ICDM). https://doi.org/10.1109/ICDM.2012.125