Package elki.outlier.lof

Class COF<O>

java.lang.Object

elki.outlier.lof.COF<O>

Type Parameters:

O - Object type

All Implemented Interfaces:

Algorithm, OutlierAlgorithm

@Title("COF: Connectivity-based Outlier Factor")
@Reference(authors="J. Tang, Z. Chen, A. W. C. Fu, D. W. Cheung",
           title="Enhancing effectiveness of outlier detections for low density patterns",
           booktitle="In Advances in Knowledge Discovery and Data Mining",
           url="https://doi.org/10.1007/3-540-47887-6_53",
           bibkey="DBLP:conf/pakdd/TangCFC02")
public class COF<O>
extends java.lang.Object
implements OutlierAlgorithm

Connectivity-based Outlier Factor (COF).

Reference:

J. Tang, Z. Chen, A. W. C. Fu, D. W. Cheung
Enhancing effectiveness of outlier detections for low density patterns.
Advances in Knowledge Discovery and Data Mining.

Since:

0.7.0

Author:

Erich Schubert

Nested Class Summary

Nested classes/interfaces inherited from interface elki.Algorithm

Algorithm.Utils

Field Summary

Fields

Modifier and Type	Field	Description
protected Distance<? super O>	distance	Distance function used.
protected int	k	The number of neighbors to query (including the query point!)
private static Logging	LOG	The logger for this class.

Constructor Summary

Constructors

Constructor	Description
COF(Distance<? super O> distance, int k)	Constructor.

Method Summary

Modifier and Type	Method	Description
protected void	computeAverageChainingDistances(KNNSearcher<DBIDRef> knnq, DistanceQuery<O> dq, DBIDs ids, WritableDoubleDataStore acds)	Computes the average chaining distance, the average length of a path through the given set of points to each target.
private void	computeCOFScores(KNNSearcher<DBIDRef> knnq, DBIDs ids, DoubleDataStore acds, WritableDoubleDataStore cofs, DoubleMinMax cofminmax)	Compute Connectivity outlier factors.
TypeInformation[]	getInputTypeRestriction()	Get the input type restriction used for negotiating the data query.
OutlierResult	run(Relation<O> relation)	Runs the COF algorithm on the given database.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface elki.outlier.OutlierAlgorithm

autorun

Field Detail

LOG

private static final Logging LOG

The logger for this class.

distance

protected Distance<? super O> distance

Distance function used.

k

protected int k

The number of neighbors to query (including the query point!)

Constructor Detail

COF

public COF(Distance<? super O> distance,
           int k)

Constructor.

Parameters:

distance - the neighborhood distance function

k - the number of neighbors to use for comparison (excluding the query point)

Method Detail

run

public OutlierResult run(Relation<O> relation)

Runs the COF algorithm on the given database.

Parameters:

relation - Data to process

Returns:

COF outlier result

computeAverageChainingDistances

protected void computeAverageChainingDistances(KNNSearcher<DBIDRef> knnq,
                                               DistanceQuery<O> dq,
                                               DBIDs ids,
                                               WritableDoubleDataStore acds)

Computes the average chaining distance, the average length of a path through the given set of points to each target. The authors of COF decided to approximate this value using a weighted mean that assumes every object is reached from the previous point (but actually every point could be best reachable from the first, in which case this does not make much sense.)

TODO: can we accelerate this by using the kNN of the neighbors?

Parameters:

knnq - KNN query

dq - Distance query

ids - IDs to process

acds - Storage for average chaining distances

computeCOFScores

private void computeCOFScores(KNNSearcher<DBIDRef> knnq,
                              DBIDs ids,
                              DoubleDataStore acds,
                              WritableDoubleDataStore cofs,
                              DoubleMinMax cofminmax)

Compute Connectivity outlier factors.

Parameters:

knnq - KNN query

ids - IDs to process

acds - Average chaining distances

cofs - Connectivity outlier factor storage

cofminmax - Score minimum/maximum tracker

getInputTypeRestriction

public TypeInformation[] getInputTypeRestriction()

Description copied from interface: Algorithm

Get the input type restriction used for negotiating the data query.

Specified by:

getInputTypeRestriction in interface Algorithm

Returns:

Type restriction