Quick adaptation to changing concepts by sensitive detection

Yoshiaki Yasumura, Naho Kitani, Kuniaki Uehara

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

2 Citations (Scopus)

Abstract

In mining data streams, one of the most challenging tasks is adapting to concept change, that is change over time of the underlying concept in the data. In this paper, we propose a novel ensemble framework for mining concept-changing data streams. This algorithm, called QACC (Quick Adaptation to Changing Concepts), realizes quick adaptation to changing concepts using an ensemble of classifiers. For quick adaptation, QACC sensitively detects concept changes in noisy streaming data. Empirical studies show that the QACC algorithm is efficient for various concept changes.

Original languageEnglish
Title of host publicationNew Trends in Applied Artificial Intelligence - 20th International Conference on Industrial, Engineering, and Other Applications of Applied Intelligent Systems, lEA/AlE 2007, Proceedings
Pages855-864
Number of pages10
Publication statusPublished - 2007 Dec 24
Event20th International Conference on Industrial, Engineering, and Other Applications of Applied Intelligent Systems, lEA/AlE-2007 - Kyoto, Japan
Duration: 2007 Jun 262007 Jun 29

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4570 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th International Conference on Industrial, Engineering, and Other Applications of Applied Intelligent Systems, lEA/AlE-2007
CountryJapan
CityKyoto
Period07/6/2607/6/29

Keywords

  • Classifier ensemble
  • Concept change
  • Data streams

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Yasumura, Y., Kitani, N., & Uehara, K. (2007). Quick adaptation to changing concepts by sensitive detection. In New Trends in Applied Artificial Intelligence - 20th International Conference on Industrial, Engineering, and Other Applications of Applied Intelligent Systems, lEA/AlE 2007, Proceedings (pp. 855-864). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4570 LNAI).