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Data Streams classification using Local Concept-adapted IOLIN System

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2008, 13(1), pp.37-44
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

김재우 1 Jaewon Song 1 Ju-Hong Lee ORD ID 1

1인하대학교

Accredited

ABSTRACT

Data stream has the tendency to change in patterns over time. Also known as concept drift, such problem can reduce the predictive performance of a classification model. CVFDT and IOLIN tried to solve the problem of a concept drift through incremental classification model updates. The local changes in patterns, however, was revealed to be unable to resolve the problems of local concept drift that occurs by influencing on total classification results. In this paper, we propose adapted IOLIN system that improves system's predictive performance by detecting the local concept drift. The experimental result shows that adaptive IOLIN, the proposed method, is about 2.8% in accuracy better than IOLIN and about 11.2% in accuracy better than CVFDT.

Citation status

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