提出了一种称为ICEA(incremental classification ensemble algorithm)的数据流挖掘算法。它利用集成分类器综合技术,实现了数据流中概念漂移的增量式检测和挖掘。实验结果表明,ICEA在处理数据流的快速概念漂移上表现出很高的精确度和较好的时间效率。
A new mining algorithm called ICEA was proposed for mining concept drifts from data streams, which used ensemble multi-classifiers to detect concept changes from the data streams in an incremental way. The experimental results show that ICEA performs higher accuracy and better time efficiency on mining concept drifts from data streams.