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离群点检测算法研究 被引量：5

Research of Outlier Detection Algorithm
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摘要 离群点检测是数据挖掘中一项重要内容,通过对当前有代表性的离群点检测算法的分析和比较,对各算法的优缺点进行了总结。针对高维数据中离群点检测算法进行了分析和研究,提出了高维数据中离群点检测需要注意的一些问题,从而便于研究者以这些算法为基础,在此基础上提出新的改进算法。 Outlier detection is an important content of data mining. This paper summarized their features by comparing and analyzing major outlier detection algorithms and gave some problems needing to be attended through analyzing and researching the outlier detection algorithms in high dimensional data. Based on these algorithms, the researchers can proceed a further analysis and propose improved algorithms.
作者 张宁
机构地区 燕山大学信息科学与工程学院
出处 《桂林电子科技大学学报》 2009年第1期22-25,共4页 Journal of Guilin University of Electronic Technology
关键词 离群点 高维数据 数据流 异常检测 outlier high--dimension data data stream anomaly detection
分类号 TP311 [自动化与计算机技术—计算机软件与理论]
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参考文献25

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二级参考文献26

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共引文献72

同被引文献80

引证文献5

二级引证文献7

桂林电子科技大学学报
2009年 第1期

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