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

作     者：Vu Anh Tran Osamu Hirose Thammakorn Saethang Lan Anh T. Nguyen Xuan Tho Dang Tu Kien T. Le Duc Luu Ngo Gavrilov Sergey Mamoru Kubo Yoichi Yamada Kenji Satou 

作者机构：Graduate School of Natural Science and Technology Kanazawa University Kanazawa Japan Institute of Science and Engineering Kanazawa University Kanazawa Japan 

出 版 物：《Journal of Software Engineering and Applications》 (软件工程与应用（英文）)

年 卷 期：2014年第7卷第8期

页      面：639-654页

学科分类：081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Attraction Clustering Data Preprocessing Density Shrinking 

摘      要：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.