Relationship between diversity and correlation in Multi-Classifier Systems

Kuo Wei Hsu, Jaideep Srivastava

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

6 Citations (Scopus)

Abstract

Diversity plays an important role in the design of Multi-Classifier Systems, but its relationship to classification accuracy is still unclear from a theoretical perspective. As a step towards the solution of this probelm, we take a different route and explore the relationship between diversity and correlation. In this paper we provide a theoretical analysis and present a nonlinear function that relates diversity to correlation, which hence can be further related to accuracy. This paper contributes to connecting existing research in diversity and correlation, and also providing a proxy to the relationship between diversity and accuracy. Our experimental results reveal deeper insights into the role of diversity in Multi-Classifier Systems.

Original languageEnglish
Title of host publicationAdvances in Knowledge Discovery and Data Mining - 14th Pacific-Asia Conference, PAKDD 2010, Proceedings
Pages500-506
Number of pages7
EditionPART 2
DOIs
Publication statusPublished - 1 Dec 2010
Event14th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2010 - Hyderabad, India
Duration: 21 Jun 201024 Jun 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6119 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference14th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2010
CountryIndia
CityHyderabad
Period21/6/1024/6/10

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Keywords

  • Correlation
  • Diversity
  • Multi-Classifier System (MCS)

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Hsu, K. W., & Srivastava, J. (2010). Relationship between diversity and correlation in Multi-Classifier Systems. In Advances in Knowledge Discovery and Data Mining - 14th Pacific-Asia Conference, PAKDD 2010, Proceedings (PART 2 ed., pp. 500-506). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6119 LNAI, No. PART 2). https://doi.org/10.1007/978-3-642-13672-6_47