IJMCR ISSN: 2321–3124
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Article Published In Vol.3 (May-June-2015)

The Detail Survey of Anomaly/Outlier Detection Methods in Data Mining

Author : Alka P.Beldar and Vinod S.Wadne

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Anomaly detection is an important problem that has been researched within diverse research areas and application domains. Many real-world applications such as intrusion or credit card fraud detection require an effective and efficient framework to identify deviated data instances. This template provides an easier and succinct understanding and comparisons between each of the outlier detection techniques for different applications. And introduce a new efficient approach which detects outlier with imperfect labels.

Keywords: Likelihood values, uncertain data.

 

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All the persons belonging directly or indirectly to Microbiology, Biotechnology, Biochemistry, Virology, Environmental Sciences, Medical and Pharmaceutical Sciences, Food and Nutrition, Botany, Zoology, Mycology, Phycology and Agricultural Sciences.