A new Algorithm for Outlier Detection based on Offset

被引：3
|
作者：
Zhang, Yue [1 ]
Liu, Jie [1 ]
Song, Bo [1 ]
机构：
[1] Shenyang Normal Univ, Software Coll, Shenyang 110034, Peoples R China
来源：
FIFTH INTERNATIONAL CONFERENCE ON INFORMATION ASSURANCE AND SECURITY, VOL 2, PROCEEDINGS | 2009年
关键词：
Outlier; Clustering; Offset; Mathematical expectation; Standard deviation;
D O I：
10.1109/IAS.2009.142
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Outlier detection is a hot topic of data mining. After studying the existing classical algorithm of detecting outliers, this paper proposes a new algorithm for outlier detection based on offset, and makes a new definition for outlier. This detection algorithm is a method based on clustering analysis. It includes cluster modeling and data detection. Also, the clustering result obtained together with detecting outliers. The experiment results on IRIS show that this algorithm can detect outliers effectively.
引用
收藏
页码：3 / 6
页数：4
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