计算机科学 ›› 2016, Vol. 43 ›› Issue (10): 63-65.doi: 10.11896/j.issn.1002-137X.2016.10.011
• 2015 第五届全国可信计算学术会议 • 上一篇 下一篇
丁智国,莫毓昌,杨凡
DING Zhi-guo, MO Yu-chang and YANG Fan
摘要: 流数据的海量、无限、分布动态变化且不均衡等特征使得对流数据的在线异常检测成为当前一个研究热点。分析了异常数据的少而不同且更容易通过随机空间的分割而孤立出来的特征,基于在线集成学习理论,提出了一种基于隔离森林的在线流数据异常检测算法。在4个UCI标准数据集上的实验结果表明提出的方法有效。
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