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Reseach Article

Survey on Outlier Detection in Data Mining

by Janpreet Singh, Shruti Aggarwal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 67 - Number 19
Year of Publication: 2013
Authors: Janpreet Singh, Shruti Aggarwal
10.5120/11506-7223

Janpreet Singh, Shruti Aggarwal . Survey on Outlier Detection in Data Mining. International Journal of Computer Applications. 67, 19 ( April 2013), 29-32. DOI=10.5120/11506-7223

@article{ 10.5120/11506-7223,
author = { Janpreet Singh, Shruti Aggarwal },
title = { Survey on Outlier Detection in Data Mining },
journal = { International Journal of Computer Applications },
issue_date = { April 2013 },
volume = { 67 },
number = { 19 },
month = { April },
year = { 2013 },
issn = { 0975-8887 },
pages = { 29-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume67/number19/11506-7223/ },
doi = { 10.5120/11506-7223 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:25:54.411704+05:30
%A Janpreet Singh
%A Shruti Aggarwal
%T Survey on Outlier Detection in Data Mining
%J International Journal of Computer Applications
%@ 0975-8887
%V 67
%N 19
%P 29-32
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Data Mining is used to extract useful information from a collection of databases or data warehouses. In recent years, Data Mining has become an important field. This paper has surveyed upon data mining and its various techniques that are used to extract useful information such as clustering, and has also surveyed the techniques that are used to detect the outliers. This paper also presents various techniques used by different researchers to detect outliers and present the efficient result to the user.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Data Mining Clustering Outlier Outlier Detection