METHODS TO DETECT DIFFERENT TYPES OF OUTLIERS

被引：0

作者：

Divya, D. ^{[1
]}

Babu, Suvanam Sasidhar ^{[2
]}

机构：

[1] Adi Shankara Inst Engn & Technol, Dept Comp Sci & Engn, Kalady, Kerala, India

[2] Sree Narayana Gurukulam Coll Engn, Dept Comp Sci & Engn, Kadayiruppu, Kerala, India

来源：

PROCEEDINGS OF 2016 INTERNATIONAL CONFERENCE ON DATA MINING AND ADVANCED COMPUTING (SAPIENCE) | 2016年

关键词：

Outliers; Outlier Mining; Tuples;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Outliers are those data that deviates significantly from the remaining data. Outliers has emerging applications in irregular credit card transactions, used to find credit card fraud, or identifying patients who shows abnormal symptoms due to suffering from a particular type of disease. This paper gives an idea about the various approaches and techniques used in outlier detection and the areas in which outlier detection is used and also about how outlier detection is handled in higher dimensional data.

引用

页码：23 / 28

页数：6

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