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ABSTRACT
Title |
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Analyzing Outlier Detection Techniques with Hybrid Method |
Authors |
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Shruti Aggarwal, Janpreet Singh |
Keywords |
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Data mining, Outlier Detection, K-Mean, Euclidean Distance, Manhattan Distance. |
Issue Date |
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September 2013 |
Abstract |
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Now day’s Outlier Detection is used in various fields such as Credit Card Fraud Detection, Cyber-Intrusion Detection, Medical Anomaly Detection, and Data Mining etc. So to detect anomaly objects from various types of dataset Outlier Detection techniques are used, that detects and remove the anomaly objects from the dataset. Outliers are the containments that divert from the other objects. Outlier detection is used to make the data knowledgeable, and easy to understand. There are various outlier detection techniques used now day that detects and remove outliers from datasets. The proposed method is used to find outliers from the numerical dataset with the mean of Euclidean and Manhattan Distance. |
Page(s) |
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1248-1252 |
ISSN |
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2229-3345 |
Source |
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Vol. 4, Issue.9 |
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