A Multi-Resolution Learning Approach to Tracking Concept Drift and Recurrent Concepts

Mihai M. Lazarescu

Abstract

This paper presents a multiple-window algorithm that combines a novel evidence based forgetting method with data prediction to handle different types of concept drift and recurrent concepts. We describe the reasoning behind the algorithm and we compare the performance with the FLORA algorithm on three different problems: the STAGGER concepts problem, a recurrent concept problem and a video surveillance problem.

References

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Paper Citation


in Harvard Style

M. Lazarescu M. (2005). A Multi-Resolution Learning Approach to Tracking Concept Drift and Recurrent Concepts . In Proceedings of the 5th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2005) ISBN 972-8865-28-7, pages 52-62. DOI: 10.5220/0002568900520062


in Bibtex Style

@conference{pris05,
author={Mihai M. Lazarescu},
title={A Multi-Resolution Learning Approach to Tracking Concept Drift and Recurrent Concepts},
booktitle={Proceedings of the 5th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2005)},
year={2005},
pages={52-62},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002568900520062},
isbn={972-8865-28-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2005)
TI - A Multi-Resolution Learning Approach to Tracking Concept Drift and Recurrent Concepts
SN - 972-8865-28-7
AU - M. Lazarescu M.
PY - 2005
SP - 52
EP - 62
DO - 10.5220/0002568900520062