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