%0 Journal Article
%A LI Shu-fang
%A LIU Dao-wei
%A QIU Xiao-feng
%A SU Jing
%A ZHANG Chun-hong
%T A Prototype-Based Adaptive Concept Drift Classification Method
%D 2017
%R 10.13190/j.jbupt.2017.03.005
%J Journal of Beijing University of Posts and Telecommunications
%P 43-50
%V 40
%N 3
%X As a frequent problem that needs to be mainly dealt with in supervised learning scenario of streaming data, the concept drift, primarily, occurs when the data distribution or the target variable changes over time. As typical data streams, the research method which real-time solves or adapts to the concept drift of data streams can provide strong support for grid security dispatch and stable control of real-time decision-making. For accurate and quick dealing with or adapting to concept drift, a prototype-based learning algorithm of data streams classification is discussed. Based on improving the problems which have been explored in existing algorithm, a new algorithm SyncPrototype was proposed,which makes new optimization in terms of methods of classification method, prototype construction and updating. Experiment shows that SyncPrototype can outperforms the existing algorithm in terms of classification performance,time performance and response rate.
%U https://journal.bupt.edu.cn/EN/10.13190/j.jbupt.2017.03.005