An Influential Algorithm for Outlier Detection

Abstract

The Subject of Data Mining, which is very vast in the direction of data analyzing , data preprocessing, data extracting, knowledge data discovery, extracting hidden data and many more. Here we discuss one of the parts of the data mining. Which is clustering, in the clustering there is the major issue to eradicate outliers from the data. Here we do work for detect outliers from the data sets. In the paper we had detailed studied about the different-different ways for detecting outliers. Likewise cluster based, distance based, density based etc. this approaches are used in the different-different methods of outlier detection (PAM, CLARA, CLARANCE, ECLARA). Here we choose the best one for further enhancement on the basis of their performance. new hybrid algorithm proposed with the classical clustering method for the improving performance on the basis of accuracy, error rate, time complexity.

Authors and Affiliations

Sachin Yele

Keywords

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  • EP ID EP242661
  • DOI -
  • Views 108
  • Downloads 0

How To Cite

Sachin Yele (2015). An Influential Algorithm for Outlier Detection. International journal of Emerging Trends in Science and Technology, 2(10), 3265-3270. https://europub.co.uk/articles/-A-242661