计算机与现代化 ›› 2010, Vol. 1 ›› Issue (11): 5-8.doi: 10.3969/j.issn.1006-2475.2010.11.002
• 算法设计与分析 • 上一篇 下一篇
刘远东,何丰
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LIU Yuan-dong, HE Feng
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摘要： 异常点是数据集中看起来与其他数据有着明显差别的点或者区域。异常点往往并不是错误，并且经常包含比较重要的信息。本文提出一种基于频繁模式的增量式异常检测方法,定义增量式异常检测异常点的性质，使用异常点因子来检测候选集，然后通过改进候选集的来进行迭代确定异常点，最后使用数据对该算法效率进行验证。
关键词: 异常点, 频繁模式, 增量式异常检测, 候选集
Abstract: An outlier in a data set is an observation or a point that is considerably dissimilar to or inconsistent with the remainder of the data. This paper presents a method to detect outliers in incremental data mining by frequent patterns, gives a description of outliers in incremental data mining, and uses a iterative process to find outlier by improving the candidate sets, and it is verified by experiments.
Key words: outlier, frequent patterns, incremental outliers-detecting, candidate sets
中图分类号:
TP301.6
刘远东;何丰. 一种基于频繁模式的增量式异常检测方法[J]. 计算机与现代化, 2010, 1(11): 5-8.
LIU Yuan-dong;HE Feng. A Method of Incremental Outliers-detecting Based on Frequent Patterns[J]. Computer and Modernization, 2010, 1(11): 5-8.
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http://www.c-a-m.org.cn/CN/Y2010/V1/I11/5
