A Study on Outlier Detection using Partition Clustering Approach |
Author(s): |
| K. Merlin Jeba , Avinashilingam University; Dr. V. Srividhya, Avinashilingam University |
Keywords: |
| Data Mining, Clustering, Partition cluster, study and Effective outlier detection |
Abstract |
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Extraction of the hidden knowledge is the data mining task. While in extraction unwanted data occurred due to the relevant extraction mechanism. Those unwanted data called outliers. Detecting the outlier is an extremely important task in a wide variety of application Domains. Outlier detection is a task that finds objects that are dissimilar or inconsistent with respect to the remaining data. Detecting the outliers, data mining uses many approaches. While clustering mechanism works effectively in the data mining approaches. For our study here use the clustering based outlier detection mechanism. Using the partitioning based clustering algorithm it analyzes the outlier data well. This paper provides a study about the various partition based clustering approach to analyzing the outliers well. |
Other Details |
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Paper ID: IJSRDV4I60409 Published in: Volume : 4, Issue : 6 Publication Date: 01/09/2016 Page(s): 875-877 |
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