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» Outlier Detection by Rareness Assumption
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CCE
2004
13 years 4 months ago
On-line outlier detection and data cleaning
Outliers are observations that do not follow the statistical distribution of the bulk of the data, and consequently may lead to erroneous results with respect to statistical analy...
Hancong Liu, Sirish Shah, Wei Jiang
BMCBI
2006
187views more  BMCBI 2006»
13 years 4 months ago
Detecting outliers when fitting data with nonlinear regression - a new method based on robust nonlinear regression and the false
Background: Nonlinear regression, like linear regression, assumes that the scatter of data around the ideal curve follows a Gaussian or normal distribution. This assumption leads ...
Harvey J. Motulsky, Ronald E. Brown
CSDA
2010
98views more  CSDA 2010»
13 years 4 months ago
Design-based estimation for geometric quantiles with application to outlier detection
Geometric quantiles are investigated using data collected from a complex survey. Geometric quantiles are an extension of univariate quantiles in a multivariate set-up that uses th...
Mohamed Chaouch, Camelia Goga
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
RAID
2009
Springer
13 years 11 months ago
Autonomic Intrusion Detection System
Abstract. We propose a novel framework of autonomic intrusion detection that fulfills online and adaptive intrusion detection in unlabeled audit data streams. The framework owns a...
Wei Wang 0012, Thomas Guyet, Svein J. Knapskog