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


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.

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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.

Conflicts of Interest

The authors declare no conflicts of interest.


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