Package  Description 

de.lmu.ifi.dbs.elki.algorithm.outlier.distance 
Distancebased outlier detection algorithms, such as DBOutlier and kNN.

Class and Description 

AbstractDBOutlier
Simple distance based outlier detection algorithms.

AbstractDBOutlier.Parameterizer
Parameterization class.

DBOutlierDetection
Simple distanced based outlier detection algorithm.

DBOutlierScore
Compute percentage of neighbors in the given neighborhood with size d.

HilOut
Fast Outlier Detection in High Dimensional Spaces
Outlier Detection using Hilbert space filling curves
Reference:
F.

HilOut.HilbertFeatures
Class organizing the data points along a hilbert curve.

HilOut.HilFeature
Hilbert representation of a single object.

HilOut.ScoreType
Type of output: all scores (upper bounds) or top n only

KNNDD
Nearest Neighbor Data Description.

KNNOutlier
Outlier Detection based on the distance of an object to its k nearest
neighbor.

KNNSOS
kNNbased adaption of Stochastic Outlier Selection.

KNNWeightOutlier
Outlier Detection based on the accumulated distances of a point to its k
nearest neighbors.

LocalIsolationCoefficient
The Local Isolation Coefficient is the sum of the kNN distance and the
average distance to its k nearest neighbors.

ODIN
Outlier detection based on the indegree of the kNN graph.

ReferenceBasedOutlierDetection
ReferenceBased Outlier Detection algorithm, an algorithm that computes kNN
distances approximately, using reference points.

SOS
Stochastic Outlier Selection.

Copyright © 2019 ELKI Development Team. License information.