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DATAMINE
2006
164views more  DATAMINE 2006»
13 years 4 months ago
Fast Distributed Outlier Detection in Mixed-Attribute Data Sets
Efficiently detecting outliers or anomalies is an important problem in many areas of science, medicine and information technology. Applications range from data cleaning to clinica...
Matthew Eric Otey, Amol Ghoting, Srinivasan Partha...
CSDA
2007
152views more  CSDA 2007»
13 years 4 months ago
Robust variable selection using least angle regression and elemental set sampling
In this paper we address the problem of selecting variables or features in a regression model in the presence of both additive (vertical) and leverage outliers. Since variable sel...
Lauren McCann, Roy E. Welsch
SAC
2009
ACM
13 years 11 months ago
Parameterless outlier detection in data streams
Outlyingness is a subjective concept relying on the isolation level of a (set of) record(s). Clustering-based outlier detection is a field that aims to cluster data and to detect...
Alice Marascu, Florent Masseglia
CSDA
2008
147views more  CSDA 2008»
13 years 4 months ago
An adjusted boxplot for skewed distributions
The boxplot is a very popular graphical tool to visualize the distribution of continuous unimodal data. It shows information about the location, spread, skewness as well as the ta...
M. Hubert, E. Vandervieren
ICDE
2011
IEEE
338views Database» more  ICDE 2011»
12 years 8 months ago
Outlier detection on uncertain data: Objects, instances, and inferences
—This paper studies the problem of outlier detection on uncertain data. We start with a comprehensive model considering both uncertain objects and their instances. An uncertain o...
Bin Jiang, Jian Pei