| Package | Description |
|---|---|
| de.lmu.ifi.dbs.elki.algorithm.outlier |
Outlier detection algorithms
|
| de.lmu.ifi.dbs.elki.algorithm.outlier.anglebased |
Angle-based outlier detection algorithms.
|
| de.lmu.ifi.dbs.elki.algorithm.outlier.clustering |
Clustering based outlier detection.
|
| de.lmu.ifi.dbs.elki.algorithm.outlier.distance |
Distance-based outlier detection algorithms, such as DBOutlier and kNN.
|
| de.lmu.ifi.dbs.elki.algorithm.outlier.distance.parallel |
Parallel implementations of distance-based outlier detectors.
|
| de.lmu.ifi.dbs.elki.algorithm.outlier.intrinsic |
Outlier detection algorithms based on intrinsic dimensionality.
|
| de.lmu.ifi.dbs.elki.algorithm.outlier.lof |
LOF family of outlier detection algorithms.
|
| de.lmu.ifi.dbs.elki.algorithm.outlier.lof.parallel |
Parallelized variants of LOF.
|
| de.lmu.ifi.dbs.elki.algorithm.outlier.meta |
Meta outlier detection algorithms: external scores, score rescaling.
|
| de.lmu.ifi.dbs.elki.algorithm.outlier.spatial |
Spatial outlier detection algorithms
|
| de.lmu.ifi.dbs.elki.algorithm.outlier.subspace |
Subspace outlier detection methods.
|
| de.lmu.ifi.dbs.elki.algorithm.outlier.svm |
Support-Vector-Machines for outlier detection.
|
| de.lmu.ifi.dbs.elki.algorithm.outlier.trivial |
Trivial outlier detection algorithms: no outliers, all outliers, label outliers.
|
| Modifier and Type | Class and Description |
|---|---|
class |
COP<V extends NumberVector>
Correlation outlier probability: Outlier Detection in Arbitrarily Oriented
Subspaces
Hans-Peter Kriegel, Peer Kröger, Erich Schubert, Arthur Zimek
Outlier Detection in Arbitrarily Oriented Subspaces in: Proc. |
class |
DWOF<O>
Algorithm to compute dynamic-window outlier factors in a database based on a
specified parameter
DWOF.Parameterizer.K_ID (-dwof.k). |
class |
GaussianModel<V extends NumberVector>
Outlier have smallest GMOD_PROB: the outlier scores is the
probability density of the assumed distribution.
|
class |
GaussianUniformMixture<V extends NumberVector>
Outlier detection algorithm using a mixture model approach.
|
class |
OPTICSOF<O>
Optics-OF outlier detection algorithm, an algorithm to find Local Outliers in
a database based on ideas from
OPTICSTypeAlgorithm clustering. |
class |
SimpleCOP<V extends NumberVector>
Algorithm to compute local correlation outlier probability.
|
| Modifier and Type | Class and Description |
|---|---|
class |
ABOD<V extends NumberVector>
Angle-Based Outlier Detection / Angle-Based Outlier Factor.
|
class |
FastABOD<V extends NumberVector>
Angle-Based Outlier Detection / Angle-Based Outlier Factor.
|
class |
LBABOD<V extends NumberVector>
Angle-Based Outlier Detection / Angle-Based Outlier Factor.
|
| Modifier and Type | Class and Description |
|---|---|
class |
EMOutlier<V extends NumberVector>
outlier detection algorithm using EM Clustering.
|
class |
KMeansOutlierDetection<O extends NumberVector>
Outlier detection by using k-means clustering.
|
class |
SilhouetteOutlierDetection<O>
Outlier detection by using the Silhouette Coefficients.
|
| Modifier and Type | Class and Description |
|---|---|
class |
AbstractDBOutlier<O>
Simple distance based outlier detection algorithms.
|
class |
DBOutlierDetection<O>
Simple distanced based outlier detection algorithm.
|
class |
DBOutlierScore<O>
Compute percentage of neighbors in the given neighborhood with size d.
|
class |
HilOut<O extends NumberVector>
Fast Outlier Detection in High Dimensional Spaces
Outlier Detection using Hilbert space filling curves
Reference:
F.
|
class |
KNNOutlier<O>
Outlier Detection based on the distance of an object to its k nearest
neighbor.
|
class |
KNNWeightOutlier<O>
Outlier Detection based on the accumulated distances of a point to its k
nearest neighbors.
|
class |
LocalIsolationCoefficient<O>
The Local Isolation Coefficient is the sum of the kNN distance and the
average distance to its k nearest neighbors.
|
class |
ODIN<O>
Outlier detection based on the in-degree of the kNN graph.
|
class |
ReferenceBasedOutlierDetection
Reference-Based Outlier Detection algorithm, an algorithm that computes kNN
distances approximately, using reference points.
|
| Modifier and Type | Class and Description |
|---|---|
class |
ParallelKNNOutlier<O>
Parallel implementation of KNN Outlier detection.
|
class |
ParallelKNNWeightOutlier<O>
Parallel implementation of KNN Weight Outlier detection.
|
| Modifier and Type | Class and Description |
|---|---|
class |
IDOS<O>
Intrinsic Dimensional Outlier Detection in High-Dimensional Data.
|
class |
IntrinsicDimensionalityOutlier<O>
Use intrinsic dimensionality for outlier detection.
|
| Modifier and Type | Class and Description |
|---|---|
class |
ALOCI<O extends NumberVector>
Fast Outlier Detection Using the "approximate Local Correlation Integral".
|
class |
COF<O>
Connectivity-based outlier factor (COF).
|
class |
FlexibleLOF<O>
Flexible variant of the "Local Outlier Factor" algorithm.
|
class |
INFLO<O>
Influence Outliers using Symmetric Relationship (INFLO) using two-way search,
is an outlier detection method based on LOF; but also using the reverse kNN.
|
class |
KDEOS<O>
Generalized Outlier Detection with Flexible Kernel Density Estimates.
|
class |
LDF<O extends NumberVector>
Outlier Detection with Kernel Density Functions.
|
class |
LDOF<O>
Computes the LDOF (Local Distance-Based Outlier Factor) for all objects of a
Database.
|
class |
LOCI<O>
Fast Outlier Detection Using the "Local Correlation Integral".
|
class |
LOF<O>
Algorithm to compute density-based local outlier factors in a database based
on a specified parameter
LOF.Parameterizer.K_ID (-lof.k). |
class |
LoOP<O>
LoOP: Local Outlier Probabilities
Distance/density based algorithm similar to LOF to detect outliers, but with
statistical methods to achieve better result stability.
|
class |
OnlineLOF<O>
Incremental version of the
LOF Algorithm, supports insertions and
removals. |
class |
SimpleKernelDensityLOF<O extends NumberVector>
A simple variant of the LOF algorithm, which uses a simple kernel density
estimation instead of the local reachability density.
|
class |
SimplifiedLOF<O>
A simplified version of the original LOF algorithm, which does not use the
reachability distance, yielding less stable results on inliers.
|
class |
VarianceOfVolume<O extends SpatialComparable>
Variance of Volume for outlier detection.
|
| Modifier and Type | Class and Description |
|---|---|
class |
ParallelLOF<O>
Parallel implementation of Local Outlier Factor using processors.
|
class |
ParallelSimplifiedLOF<O>
Parallel implementation of Simplified-LOF Outlier detection using processors.
|
| Modifier and Type | Class and Description |
|---|---|
class |
ExternalDoubleOutlierScore
External outlier detection scores, loading outlier scores from an external
file.
|
class |
FeatureBagging
A simple ensemble method called "Feature bagging" for outlier detection.
|
class |
HiCS<V extends NumberVector>
Algorithm to compute High Contrast Subspaces for Density-Based Outlier
Ranking.
|
class |
RescaleMetaOutlierAlgorithm
Scale another outlier score using the given scaling function.
|
class |
SimpleOutlierEnsemble
Simple outlier ensemble method.
|
| Modifier and Type | Field and Description |
|---|---|
private OutlierAlgorithm |
HiCS.outlierAlgorithm
Outlier detection algorithm.
|
private OutlierAlgorithm |
HiCS.Parameterizer.outlierAlgorithm
Holds the value of
HiCS.Parameterizer.ALGO_ID. |
| Modifier and Type | Field and Description |
|---|---|
private List<OutlierAlgorithm> |
SimpleOutlierEnsemble.algorithms
The algorithms to run.
|
private List<OutlierAlgorithm> |
SimpleOutlierEnsemble.Parameterizer.algorithms
The algorithms to run.
|
| Constructor and Description |
|---|
HiCS(int m,
double alpha,
OutlierAlgorithm outlierAlgorithm,
GoodnessOfFitTest statTest,
int cutoff,
RandomFactory rnd)
Constructor.
|
| Constructor and Description |
|---|
SimpleOutlierEnsemble(List<OutlierAlgorithm> algorithms,
EnsembleVoting voting)
Constructor.
|
| Modifier and Type | Class and Description |
|---|---|
class |
AbstractDistanceBasedSpatialOutlier<N,O>
Abstract base class for distance-based spatial outlier detection methods.
|
class |
AbstractNeighborhoodOutlier<O>
Abstract base class for spatial outlier detection methods using a spatial
neighborhood.
|
class |
CTLuGLSBackwardSearchAlgorithm<V extends NumberVector>
GLS-Backward Search is a statistical approach to detecting spatial outliers.
|
class |
CTLuMeanMultipleAttributes<N,O extends NumberVector>
Mean Approach is used to discover spatial outliers with multiple attributes.
|
class |
CTLuMedianAlgorithm<N>
Median Algorithm of C.
|
class |
CTLuMedianMultipleAttributes<N,O extends NumberVector>
Median Approach is used to discover spatial outliers with multiple
attributes.
|
class |
CTLuMoranScatterplotOutlier<N>
Moran scatterplot outliers, based on the standardized deviation from the
local and global means.
|
class |
CTLuRandomWalkEC<P>
Spatial outlier detection based on random walks.
|
class |
CTLuScatterplotOutlier<N>
Scatterplot-outlier is a spatial outlier detection method that performs a
linear regression of object attributes and their neighbors average value.
|
class |
CTLuZTestOutlier<N>
Detect outliers by comparing their attribute value to the mean and standard
deviation of their neighborhood.
|
class |
SLOM<N,O>
SLOM: a new measure for local spatial outliers
Reference:
Sanjay Chawla and Pei Sun SLOM: a new measure for local spatial outliers in Knowledge and Information Systems 9(4), 412-429, 2006 This implementation works around some corner cases in SLOM, in particular when an object has none or a single neighbor only (albeit the results will still not be too useful then), which will result in divisions by zero. |
class |
SOF<N,O>
The Spatial Outlier Factor (SOF) is a spatial
LOF variation. |
class |
TrimmedMeanApproach<N>
A Trimmed Mean Approach to Finding Spatial Outliers.
|
| Modifier and Type | Class and Description |
|---|---|
class |
AbstractAggarwalYuOutlier<V extends NumberVector>
Abstract base class for the sparse-grid-cell based outlier detection of
Aggarwal and Yu.
|
class |
AggarwalYuEvolutionary<V extends NumberVector>
Evolutionary variant (EAFOD) of the high-dimensional outlier detection
algorithm by Aggarwal and Yu.
|
class |
AggarwalYuNaive<V extends NumberVector>
BruteForce variant of the high-dimensional outlier detection algorithm by
Aggarwal and Yu.
|
class |
OutRankS1
OutRank: ranking outliers in high dimensional data.
|
class |
OUTRES<V extends NumberVector>
Adaptive outlierness for subspace outlier ranking (OUTRES).
|
class |
SOD<V extends NumberVector>
Subspace Outlier Degree.
|
| Modifier and Type | Class and Description |
|---|---|
class |
LibSVMOneClassOutlierDetection<V extends NumberVector>
Outlier-detection using one-class support vector machines.
|
| Modifier and Type | Class and Description |
|---|---|
class |
ByLabelOutlier
Trivial algorithm that marks outliers by their label.
|
class |
TrivialAllOutlier
Trivial method that claims all objects to be outliers.
|
class |
TrivialAverageCoordinateOutlier
Trivial method that takes the average of all dimensions (for one-dimensional
data that is just the actual value!)
|
class |
TrivialGeneratedOutlier
Extract outlier score from the model the objects were generated by.
|
class |
TrivialNoOutlier
Trivial method that claims to find no outliers.
|
Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.