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

Class ODIN<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.ODIN<O>

Type Parameters:

O - Object type

All Implemented Interfaces:

Algorithm, DistanceBasedAlgorithm<O>, OutlierAlgorithm

@Title(value="ODIN: Outlier Detection Using k-Nearest Neighbour Graph")
 @Reference(authors="V. Hautam\u00e4ki, I. K\u00e4rkk\u00e4inen, P. Fr\u00e4nti",
           title="Outlier detection using k-nearest neighbour graph",
           booktitle="Proc. 17th Int. Conf. Pattern Recognition (ICPR 2004)",
           url="https://doi.org/10.1109/ICPR.2004.1334558",
           bibkey="DBLP:conf/icpr/HautamakiKF04")
 @Alias(value="de.lmu.ifi.dbs.elki.algorithm.outlier.ODIN")
public class ODIN<O>
extends AbstractDistanceBasedAlgorithm<O,OutlierResult>
implements OutlierAlgorithm

Outlier detection based on the in-degree of the kNN graph.

This is a curried version: instead of using a threshold T to obtain a binary decision, we use the computed value as outlier score; normalized by k to make the numbers more comparable across different parameterizations.

Reference:

V. Hautamäki and I. Kärkkäinen and P. Fränti
Outlier detection using k-nearest neighbour graph
Proc. 17th Int. Conf. Pattern Recognition (ICPR 2004)

Since:

0.6.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

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

Field Summary

Fields

Modifier and Type	Field and Description
(package private) int	k Number of neighbors for kNN graph.
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
ODIN(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) Run the ODIN algorithm

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

LOG

private static final Logging LOG

Class logger.

k

int k

Number of neighbors for kNN graph.

Constructor Detail

ODIN

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

Constructor.

Parameters:

distanceFunction - Distance function

k - k parameter

Method Detail

run

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

Run the ODIN algorithm

Parameters:

database - Database to run on.

relation - Relation to process.

Returns:

ODIN outlier result.

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

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