Outlier Detection using Hybrid ECLARANS-DB-Scan Clustering Algorithm in Data Mining |
Author(s): |
| Shivi Bhardwaj , United College Of Engineering & Research Greater Noida |
Keywords: |
| Data mining, outlier detection, clustering, ECLARANS-DB-scan clustering, numerical data etc |
Abstract |
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Data mining is the extraction of hidden predictive information from large dataset and also a powerful new technology with great potential to analyze important information in the data warehouses. Data objects which do not comply with the general behavior or model of the data are called Outliers. Outlier Detection in dataset has numerous applications such as fraud detection, customized marketing, and the search for terrorism. However, the use of Outlier Detection for various purposes is not an easy task. In this paper, we propose a technique for detecting outliers in an easier manner using ECLARANS-DB-scan clustering. We analyze our technique to clearly distinguish the numerical data from outliers. |
Other Details |
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Paper ID: IJSRDV5I40910 Published in: Volume : 5, Issue : 4 Publication Date: 01/07/2017 Page(s): 1305-1309 |
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