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CSDA
2008
158views more  CSDA 2008»
13 years 5 months ago
Outlier identification in high dimensions
A computationally fast procedure for identifying outliers is presented, that is particularly effective in high dimensions. This algorithm utilizes simple properties of principal c...
Peter Filzmoser, Ricardo A. Maronna, Mark Werner
IJON
2006
85views more  IJON 2006»
13 years 4 months ago
From outliers to prototypes: Ordering data
We propose simple and fast methods based on nearest neighbors that order objects from high-dimensional data sets from typical points to untypical points. On the one hand, we show ...
Stefan Harmeling, Guido Dornhege, David M. J. Tax,...
KDD
2009
ACM
189views Data Mining» more  KDD 2009»
13 years 11 months ago
CoCo: coding cost for parameter-free outlier detection
How can we automatically spot all outstanding observations in a data set? This question arises in a large variety of applications, e.g. in economy, biology and medicine. Existing ...
Christian Böhm, Katrin Haegler, Nikola S. M&u...
CIKM
2010
Springer
13 years 3 months ago
SHRINK: a structural clustering algorithm for detecting hierarchical communities in networks
Community detection is an important task for mining the structure and function of complex networks. Generally, there are several different kinds of nodes in a network which are c...
Jianbin Huang, Heli Sun, Jiawei Han, Hongbo Deng, ...
TNN
2010
148views Management» more  TNN 2010»
12 years 11 months ago
A fast algorithm for robust mixtures in the presence of measurement errors
Abstract--In experimental and observational sciences, detecting atypical, peculiar data from large sets of measurements has the potential of highlighting candidates of interesting ...
Jianyong Sun, Ata Kabán