Detecting pattern-based outliers

Detecting pattern-based outliers
复制标题

DOI:
10.1016/s0167-8655(03)00165-x
复制
发表时间:
2003-12
期刊:
Pattern Recognit. Lett.
影响因子:
--
通讯作者:
Tianming Hu;S. Sung
Tianming Hu;S. Sung
中科院分区:
其他
文献类型:
--
作者:
Tianming Hu;S. Sung

文献摘要

被引文献

相似文献

异常值检测针对那些偏离一般模式的异常数据。除了高密度聚类之外,还有另一种模式称为低密度规则性。因此,有两种类型的异常值。他们。我们提出两种技术:一种用于识别两种模式,另一种用于检测相应的异常值。
Outlier detection targets those exceptional data that deviate from the general pattern. Besides high density clustering, there is another pattern called low density regularity. Thus, there are two types of outliers w.r.t. them. We propose two techniques: one to identify the two patterns and the other to detect the corresponding outliers.