关键词: 四分位距, Hoeffding不等式, 数据流分类, 概念漂移

Abstract:

In view of the problem that most of the concept drift detection algorithms have high latency and are too sensitive to noise, a concept drift detection method based on the quartile interval overlapping sliding window is proposed, which uses the samples in the quartile window and the improved Hoeffding inequality to detect the concept drift. In order to avoid the influence of noise on the classifier performance, a dynamic coefficient based on the current sample classification accuracy is introduced into the Hoeffding inequality. Experimental results show that the improved method can effectively improve concept drift detection accuracy and reduce drift detection delay.

Key words: interquartile range, Hoeffding inequality, data stream classification, concept drift