Detecting pattern-based outliers
作者： Tianming Hu , Sam Y Sung
DOI: 10.1016/S0167-8655(03)00165-X
关键词:
摘要: Outlier detection targets those exceptional data that deviate from the general pattern. Besides high density clustering, there is another pattern called low regularity. Thus, are two types of outliers w.r.t. them. We propose techniques: one to identify patterns and other detect corresponding outliers.
acm.org
elsevier.com
sci-hub.se 参考文章(16)
Peter Diggle, A Kernel Method for Smoothing Point Process Data Applied Statistics. ,vol. 34, pp. 138- 147 ,(1985) , 10.2307/2347366
Hans-Peter Kriegel, Martin Ester, Jörg Sander, Xiaowei Xu, A density-based algorithm for discovering clusters in large spatial Databases with Noise knowledge discovery and data mining. pp. 226- 231 ,(1996)
Vic Barnett, Toby Lewis, Outliers in Statistical Data ,(1978)
Rakesh Agrawal, Johannes Gehrke, Dimitrios Gunopulos, Prabhakar Raghavan, Automatic subspace clustering of high dimensional data for data mining applications Proceedings of the 1998 ACM SIGMOD international conference on Management of data - SIGMOD '98. ,vol. 27, pp. 94- 105 ,(1998) , 10.1145/276304.276314
Douglas M. Hawkins, Identification of outliers ,(1980)
Charu C. Aggarwal, Philip S. Yu, Outlier detection for high dimensional data international conference on management of data. ,vol. 30, pp. 37- 46 ,(2001) , 10.1145/375663.375668
Edwin M. Knorr, Raymond T. Ng, Vladimir Tucakov, Distance-based outliers: algorithms and applications very large data bases. ,vol. 8, pp. 237- 253 ,(2000) , 10.1007/S007780050006
Sheldon M Ross, Sheldon M Ross, Sheldon M Ross, Sheldon M Ross, Etats-Unis Mathématicien, A First Course in Probability ,(1976)
Raymond T. Ng, Jiawei Han, CLARANS: a method for clustering objects for spatial data mining IEEE Transactions on Knowledge and Data Engineering. ,vol. 14, pp. 1003- 1016 ,(2002) , 10.1109/TKDE.2002.1033770
Noel A. C. Cressie, Noel A. C. Cressie, Statistics for spatial data ,(1991)