Distance-based outlier detection algorithms, such as DBOutlier and kNN.
|Class and Description|
Simple distance based outlier detection algorithms.
Simple distanced based outlier detection algorithm.
Compute percentage of neighbors in the given neighborhood with size d.
Fast Outlier Detection in High Dimensional Spaces Outlier Detection using Hilbert space filling curves Reference: F.
Class organizing the data points along a hilbert curve.
Hilbert representation of a single object.
Type of output: all scores (upper bounds) or top n only
Nearest Neighbor Data Description.
Outlier Detection based on the distance of an object to its k nearest neighbor.
kNN-based adaption of Stochastic Outlier Selection.
Outlier Detection based on the accumulated distances of a point to its k nearest neighbors.
The Local Isolation Coefficient is the sum of the kNN distance and the average distance to its k nearest neighbors.
Outlier detection based on the in-degree of the kNN graph.
Reference-Based Outlier Detection algorithm, an algorithm that computes kNN distances approximately, using reference points.
Stochastic Outlier Selection.
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