Partition Based with Outlier Detection

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2018 by IJCTT Journal
Volume-59 Number-1
Year of Publication : 2018
Authors : Saswati Bhattacharyya,RakeshK. Das,Nilutpol Sonowal,Aloron Bezbaruah, Rabinder K. Prasad
  10.14445/22312803/IJCTT-V59P110

MLA

Saswati Bhattacharyya,RakeshK. Das,Nilutpol Sonowal,Aloron Bezbaruah, Rabinder K. Prasad "Partition Based with Outlier Detection". International Journal of Computer Trends and Technology (IJCTT) V59(1):63-67, May 2018. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract
Partition based method is widely used in every field of science and technology. It can detect spherical shaped clusters, but cannot detect any noisy information that is present in a data set. In this paper, we have proposed a partition based method with an outlier detection feature which can detect good quality clusters as well as identify the outliers present in it in optimal time. We have figured the outlier detection issue for the most part and planned calculations which can precisely identify anomalies in a way that the time complexity ought to be least. We have calculated the degree of outlier of each data object and included in existing partition based clustering technique to get good quality clusters along with the required anomalies. Additionally, utilizing a real world data set, we will exhibit that our methodologies can abstain from distinguishing false anomalies as well as discover genuine outliers overlooked by existing techniques.

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Keywords
Partition-based Clustering, Outlier detection, degree of outlier, k-Mean