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2015 1

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Anensemble method for data stream classification in the presence of concept drift

Omid ABBASZADEH,Ali AMIRI,Ali Reza KHANTEYMOORI

《信息与电子工程前沿（英文）》 2015年 第16卷 第12期   页码 1059-1068 doi: 10.1631/FITEE.1400398

摘要： One recent area of interest in computer science is data stream management and processing. By ‘data stream’, we refer to continuous and rapidly generated packages of data. Specific features of data streams are immense volume, high production rate, limited data processing time, and data concept drift; these features differentiate the data stream from standard types of data. An issue for the data stream is classification of input data. A novel ensemble classifier is proposed in this paper. The classifier uses base classifiers of two weighting functions under different data input conditions. In addition, a new method is used to determine drift, which emphasizes the precision of the algorithm. Another characteristic of the proposed method is removal of different numbers of the base classifiers based on their quality. Implementation of a weighting mechanism to the base classifiers at the decision-making stage is another advantage of the algorithm. This facilitates adaptability when drifts take place, which leads to classifiers with higher efficiency. Furthermore, the proposed method is tested on a set of standard data and the results confirm higher accuracy compared to available ensemble classifiers and single classifiers. In addition, in some cases the proposed classifier is faster and needs less storage space.

关键词： Data stream     Classificaion     Ensemble classifiers     Concept drift    

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Anensemble method for data stream classification in the presence of concept drift

Omid ABBASZADEH,Ali AMIRI,Ali Reza KHANTEYMOORI

期刊论文