Recurring Concept Detection and Prediction Based on the Graph

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Recurring Concept Detection and Prediction Based on the Graph

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[1]Baiyang,Wang Zhihai,Sun Yange.Recurring Concept Detection and Prediction Based on the Graph[J].Journal of Zhengzhou University (Engineering Science),2017,38(04):57-64.[doi:10.13705/j.issn.1671-6833.2017.01.021]

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Journal of Zhengzhou University (Engineering Science)[ISSN 1671-6833/CN 41-1339/T] Volume: 38 Number of periods: 2017 04 Page number: 57-64 Column: Public date: 2017-07-18

Title:: Recurring Concept Detection and Prediction Based on the Graph

Author(s):: Baiyang1; Wang Zhihai1; Sun Yange2; 1. School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044; 2. School of Computer and Information Technology, Xinyang Normal University, Xinyang, Henan 464000

Keywords:: data stream; data mining; concept drift; drift detection; recurring concept

CLC:: -

DOI:: 10.13705/j.issn.1671-6833.2017.01.021

Abstract:: Concept drift was a challenging problem in stream mining.When the concept drift occured,the accuracy of the original predictive model may decrease significantly.So it was necessary to put forward a feasible method to detect concept drift.Recurring concept is a special case of concept drift.However,most of existing algorithms have not taken full account of this case.This research proposed an approach to the recurring concept detection problem.Extensive experiment revealed that the method we proposed could detect not only the concept drift with relatively low delay and rate of false positive,but also the recurring concepts.Moreover,the accuracy of the classification would be greatly improved.

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