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New ensemble method for classification of data streams
Sobhani, P.
- DOI:10.1109/ICCKE.2011.6413362
- Main Entry: Sobhani, P.
- Title:New ensemble method for classification of data streams.
- Abstract:Classification of data streams has become an important area of data mining, as the number of applications facing these challenges increases. In this paper, we propose a new ensemble learning method for data stream classification in presence of concept drift. Our method is capable of detecting changes and adapting to new concepts which appears in the stream
- Notes:Sharif Repository
- Subject:Boosting.
- Subject:Concept drift.
- Subject:Data stream classification.
- Subject:Ensemble learning.
- Subject:Classification of data.
- Subject:Concept drifts.
- Subject:Data stream classifications.
- Subject:Ensemble learning.
- Subject:Ensemble methods.
- Subject:Data communication systems.
- Subject:Knowledge engineering.
- Subject:Data mining.
- Added Entry:Beigy, H.
- Added Entry:Sharif University of Technology.
- Added Entry:2011 1st International eConference on Computer and Knowledge Engineering, Mashhad; Iran; 13 October 2011 through 14 October 2011; Category numberCFP1194T-ART
- Added Entry:ICCKE 2011
- Source: 2011 1st International eConference on Computer and Knowledge Engineering, ICCKE 2011, Mashhad, 13 October 2011 through 14 October 2011 ; 2011 , Pages 264-269 ; 9781467357135 (ISBN)
- Web Site:http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6413362