de.lmu.ifi.dbs.elki.algorithm.outlier.distance.parallel

Class ParallelKNNOutlier<O>

java.lang.Object

de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm<R>

de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm<O,OutlierResult>

de.lmu.ifi.dbs.elki.algorithm.outlier.distance.parallel.ParallelKNNOutlier<O>

Type Parameters:

O - Object type

All Implemented Interfaces:

Algorithm, DistanceBasedAlgorithm<O>, OutlierAlgorithm

@Reference(authors="Erich Schubert, Arthur Zimek, Hans-Peter Kriegel",
           title="Local Outlier Detection Reconsidered: a Generalized View on Locality with Applications to Spatial, Video, and Network Outlier Detection",
           booktitle="Data Mining and Knowledge Discovery 28(1)",
           url="https://doi.org/10.1007/s10618-012-0300-z",
           bibkey="DBLP:journals/datamine/SchubertZK14")
public class ParallelKNNOutlier<O>
extends AbstractDistanceBasedAlgorithm<O,OutlierResult>
implements OutlierAlgorithm

Parallel implementation of KNN Outlier detection.

Reference:

S. Ramaswamy, R. Rastogi, K. Shim
Efficient Algorithms for Mining Outliers from Large Data Sets
Proc. of the Int. Conf. on Management of Data

This parallelized implementation is based on the easy-to-parallelize generalized pattern discussed in

Erich Schubert, Arthur Zimek, Hans-Peter Kriegel
Local Outlier Detection Reconsidered: a Generalized View on Locality with Applications to Spatial, Video, and Network Outlier Detection
Data Mining and Knowledge Discovery 28(1)

Since:

0.7.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	ParallelKNNOutlier.Parameterizer<O> Parameterization class

Field Summary

Fields

Modifier and Type	Field and Description
private int	k Parameter k
private static Logging	LOG Class logger

Fields inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm

ALGORITHM_ID

Fields inherited from interface de.lmu.ifi.dbs.elki.algorithm.DistanceBasedAlgorithm

DISTANCE_FUNCTION_ID

Constructor Summary

Constructors

Constructor and Description
ParallelKNNOutlier(DistanceFunction<? super O> distanceFunction, int k) Constructor.

Method Summary

Modifier and Type	Method and Description
TypeInformation[]	getInputTypeRestriction() Get the input type restriction used for negotiating the data query.
protected Logging	getLogger() Get the (STATIC) logger for this class.
OutlierResult	run(Database database, Relation<O> relation)

Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm

getDistanceFunction

Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm

run

Methods inherited from class java.lang.Object

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

Methods inherited from interface de.lmu.ifi.dbs.elki.algorithm.outlier.OutlierAlgorithm

run

Field Detail

k

private int k

Parameter k

LOG

private static final Logging LOG

Class logger

Constructor Detail

ParallelKNNOutlier

public ParallelKNNOutlier(DistanceFunction<? super O> distanceFunction,
                          int k)

Constructor.

Parameters:

distanceFunction - Distance function

k - K parameter

Method Detail

getInputTypeRestriction

public TypeInformation[] getInputTypeRestriction()

Description copied from class: AbstractAlgorithm

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

Specified by:

getInputTypeRestriction in interface Algorithm

Specified by:

getInputTypeRestriction in class AbstractAlgorithm<OutlierResult>

Returns:

Type restriction

run

public OutlierResult run(Database database,
                         Relation<O> relation)

getLogger

protected Logging getLogger()

Description copied from class: AbstractAlgorithm

Get the (STATIC) logger for this class.

Specified by:

getLogger in class AbstractAlgorithm<OutlierResult>

Returns:

the static logger