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An Enhanced Detection of Outlier using Independent Component Analysis among Multiple Data Instances via Oversampling

Anomaly is a pattern of data that does not conforms to expected behavior. It is also referred as outlier, exceptions, peculiarities, surprise etc. Anomaly detection aims to identify a small group of instances which deviates from the existing data. It needs to solve an unsupervised yet unstable data learning problem. Detecting an anomaly is an essential research topic in data mining to solve the real world applications like intrusion detection, homeland security to identify the deviated data instances.

Provided by: Iosrjournals Topic: Big Data Date Added: Apr 2014 Format: PDF

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