Uses of Package
de.lmu.ifi.dbs.elki.algorithm.outlier.distance

Packages that use de.lmu.ifi.dbs.elki.algorithm.outlier.distance

Package	Description
de.lmu.ifi.dbs.elki.algorithm.outlier.distance	Distance-based outlier detection algorithms, such as DBOutlier and kNN.

Classes in de.lmu.ifi.dbs.elki.algorithm.outlier.distance used by de.lmu.ifi.dbs.elki.algorithm.outlier.distance

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
KNNOutlier Outlier Detection based on the distance of an object to its k nearest neighbor.
KNNWeightOutlier Outlier Detection based on the accumulated distances of a point to its k nearest neighbors.
ODIN Outlier detection based on the in-degree of the kNN graph.
ReferenceBasedOutlierDetection Reference-Based Outlier Detection algorithm, an algorithm that computes kNN distances approximately, using reference points.