International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 97 - Number 8 |
Year of Publication: 2014 |
Authors: Kamal Malik, H. Sadawarti, Kalra G. S |
10.5120/17026-7318 |
Kamal Malik, H. Sadawarti, Kalra G. S . Comparative Analysis of Outlier Detection Techniques. International Journal of Computer Applications. 97, 8 ( July 2014), 12-21. DOI=10.5120/17026-7318
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.