Downloads: 118 | Views: 224

Review Papers | Computer Science & Engineering | India | Volume 3 Issue 12, December 2014

A Critical Review on Outlier Detection Techniques

Poonam Rana | Deepika Pahuja ^[2] | Ritu Gautam ^[2]

Abstract: Outlier Detection is a Data Mining Application. Outlier contains noisy data which is researched in various domains. The various techniques are already being researched that is more generic. We surveyed on various techniques and applications of outlier detection that provides a novel approach that is more useful for the beginners. The proposed approach helps to clean data at university level in less time with great accuracy. This survey includes the existing outlier techniques and applications where the noisy data exists. Our paper defines critical review on various techniques used in different applications of outlier detection that are to be researched further and they gives a particular type of knowledge based data i. e. more useful in research activities. So where the Anomalies is present it will be detected through outlier detection techniques and monitored accordingly especially in educational Data Mining.

Keywords: Outlier, Outlier Detection, Anomaly, Self and Card watch

Edition: Volume 3 Issue 12, December 2014,

Pages: 2394 - 2403