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D-IMPACT: A Data Preprocessing Algorithm to Improve the Performance of Clustering

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DOI: 10.4236/jsea.2014.78059    3,319 Downloads   4,766 Views   Citations


In this study, we propose a data preprocessing algorithm called D-IMPACT inspired by the IMPACT clustering algorithm. D-IMPACT iteratively moves data points based on attraction and density to detect and remove noise and outliers, and separate clusters. Our experimental results on two-dimensional datasets and practical datasets show that this algorithm can produce new datasets such that the performance of the clustering algorithm is improved.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Tran, V. , Hirose, O. , Saethang, T. , Nguyen, L. , Dang, X. , Le, T. , Ngo, D. , Sergey, G. , Kubo, M. , Yamada, Y. and Satou, K. (2014) D-IMPACT: A Data Preprocessing Algorithm to Improve the Performance of Clustering. Journal of Software Engineering and Applications, 7, 639-654. doi: 10.4236/jsea.2014.78059.


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