Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0167-8655(03)00165-X
Title: Detecting pattern-based outliers
Authors: Hu, T.
Sung, S.Y. 
Keywords: Clustering
Complete spatial randomness
Outlier detection
Regular spacing
Issue Date: 2003
Source: Hu, T., Sung, S.Y. (2003). Detecting pattern-based outliers. Pattern Recognition Letters 24 (16) : 3059-3068. ScholarBank@NUS Repository. https://doi.org/10.1016/S0167-8655(03)00165-X
Abstract: Outlier detection targets those exceptional data that deviate from the general pattern. Besides high density clustering, there is another pattern called low density regularity. Thus, there are two types of outliers w.r.t. them. We propose two techniques: one to identify the two patterns and the other to detect the corresponding outliers. © 2003 Elsevier B.V. All rights reserved.
Source Title: Pattern Recognition Letters
URI: http://scholarbank.nus.edu.sg/handle/10635/38959
ISSN: 01678655
DOI: 10.1016/S0167-8655(03)00165-X
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

27
checked on Dec 5, 2017

WEB OF SCIENCETM
Citations

17
checked on Dec 5, 2017

Page view(s)

61
checked on Dec 11, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.