一种自适应局部概念漂移的数据流分类算法

计算机科学 ›› 2008, Vol. 35 ›› Issue (2): 138-139.

一种自适应局部概念漂移的数据流分类算法

尹志武黄上腾

上海交通大学计算机科学与工程系,上海200240

出版日期:2018-11-16 发布日期:2018-11-16

YIN Zhi-Wu ,HUANG Shang-Teng （Department of Computer Science and Engineering, Shanghai Jiaotong University, Shanghai 200240）

Online:2018-11-16 Published:2018-11-16

摘要/Abstract

摘要： 本文基于DB2算法提出一个能实时检测局部概念漂移，并随之自适应调整的数据流分类算法IncreDB2。该算法动态增量维护一个层次分类树。当局部概念漂移出现时，IncreDB2不是重新构造一个全新的分类树，而是仅更新漂移所影响到的局部结点，具有较高的时间效率。实验结果表明了该算法的正确性和有效性。

关键词: 数据流挖掘多分类局部概念漂移

Abstract: Based on the DB2 method, an adaptive method called IncreDB2 is proposed to detect and adapt to local concept drift continuously in data stream classification This method dynamically maintains a hierarchical classification tree. When local concept drift is

Key words: Data stream mining, Multi-classification, Local concept drift

尹志武黄上腾. 一种自适应局部概念漂移的数据流分类算法[J]. 计算机科学, 2008, 35(2): 138-139. https://doi.org/

YIN Zhi-Wu ,HUANG Shang-Teng （Department of Computer Science and Engineering, Shanghai Jiaotong University, Shanghai 200240）. [J]. Computer Science, 2008, 35(2): 138-139. https://doi.org/

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