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Comparative Analysis of Outlier Detection Techniques

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International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 97 - Number 8
Year of Publication: 2014
Authors:
Kamal Malik
H. Sadawarti
Kalra G. S
10.5120/17026-7318

Kamal Malik, H Sadawarti and Kalra G S. Article: Comparative Analysis of Outlier Detection Techniques. International Journal of Computer Applications 97(8):12-21, July 2014. Full text available. BibTeX

@article{key:article,
	author = {Kamal Malik and H. Sadawarti and Kalra G. S},
	title = {Article: Comparative Analysis of Outlier Detection Techniques},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {97},
	number = {8},
	pages = {12-21},
	month = {July},
	note = {Full text available}
}

Abstract

Data Mining simply refers to the extraction of very interesting patterns of the data from the massive data sets. Outlier detection is one of the important aspects of data mining which actually finds out the observations that are deviating from the common expected behavior. Outlier detection and analysis is sometimes known as outlier mining. In this paper, we have tried to provide the broad and a comprehensive literature survey of outliers and outlier detection techniques under one roof, so as to explain the richness and complexity associated with each outlier detection technique. Moreover, we have also given a broad comparison of the various methods of the different outlier techniques.

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