
LOF
 Referenced in 90 articles
[sw19311]
 Identifying densitybased local outliers. For many KDD applications, such as detecting criminal activities ... commerce, finding the rare instances or the outliers, can be more interesting than finding ... common patterns. Existing work in outlier detection regards being an outlier as a binary property ... each object a degree of being an outlier. This degree is called the local outlier...

ROBPCA
 Referenced in 67 articles
[sw11592]
 diagnostic plot that displays and classifies the outliers. We apply the algorithm to several datasets...

Orca
 Referenced in 32 articles
[sw32638]
 Orca: A Program for Mining DistanceBased Outliers. Orca is a program for mining outliers ... large multivariate data sets. An outlier is an example that is substantially different from ... reminder of the data. An outlier may have values for an attribute that are unusually ... rarely seen together. Orca mines distancebased outliers. That is, Orca uses the distance from...

mvBACON
 Referenced in 27 articles
[sw36501]
 BACON: blocked adaptive computationally efficient outlier nominators. Although it is customary to assume that data ... homogeneous, in fact, they often contain outliers or subgroups. Methods for identifying multiple outliers ... sophisticated methods, the computation cost often makes outlier detection unattractive. All multiple outlier detection methods ... this paper (algorithms for the detection of outliers in multivariate and regression data). The algorithms...

LIBRA
 Referenced in 28 articles
[sw10553]
 robust procedures. These methods are resistant to outliers in the data. Currently, the library contains ... Squares Regression (RSIMPLS), classification (RDA, RSIMCA), clustering, outlier detection for skewed data (including the bagplot ... tools are provided for model checking and outlier detection. Most of the functions require...

MOA
 Referenced in 41 articles
[sw11966]
 machine learning algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems...

Rainbow
 Referenced in 33 articles
[sw01263]
 data sets for functional data display and outlier detection...

MixSim
 Referenced in 33 articles
[sw07914]
 simulating Gaussian and nonGaussian data, simulating outliers and noise variables, calculating various measures...

TRAMO
 Referenced in 25 articles
[sw24172]
 Regression with ARlMA Noise, Missing Observations, and Outliers...

FSDA
 Referenced in 18 articles
[sw11737]
 pharmaceutical problems, where the presence of outliers, multiple groups, deviations from normality and other complex...

wwcode
 Referenced in 18 articles
[sw26044]
 data deviate from normality and/or contain outliers. These procedures can be generalized by introducing weights...

MVN
 Referenced in 16 articles
[sw20752]
 tests and graphical approaches and implements multivariate outlier detection and univariate normality of marginal distributions...

tlmec
 Referenced in 11 articles
[sw11119]
 errors, such assumptions make inferences vulnerable to outliers. The sensitivity to outliers and the need...

GET
 Referenced in 15 articles
[sw35164]
 regions of functional or multivariate data (e.g. outlier detection, functional boxplot) and for global confidence...

Sheppack
 Referenced in 13 articles
[sw07352]
 when the data is known to contain outliers. SHEPPACK also includes a hybrid robust piecewise...

PCL
 Referenced in 13 articles
[sw22770]
 used, for example, to filter outliers from noisy data, stitch 3D point clouds together, segment...

ELKI
 Referenced in 13 articles
[sw30860]
 unsupervised methods in cluster analysis and outlier detection. In order to achieve high performance...

outliers
 Referenced in 7 articles
[sw07333]
 package outliers: Tests for outliers. A collection of some tests commonly used for identifying outliers...

robCompositions
 Referenced in 12 articles
[sw11804]
 methods, methods to impute rounded zeros, (robust) outlier detection for compositional data, (robust) principal component...

SLOM
 Referenced in 6 articles
[sw36331]
 SLOM: a new measure for local spatial outliers. We propose a measure, spatial local outlier ... able to discern local spatial outliers that are usually missed by global techniques, like “three ... data point and suppresses the reporting of outliers in highly unstable areas, where data ... heterogeneous and the notion of outliers is not meaningful. We prove several properties of SLOM...