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

Class KNNOutlier<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.KNNOutlier<O>

Type Parameters:

O - the type of objects handled by this algorithm

All Implemented Interfaces:

Algorithm, DistanceBasedAlgorithm<O>, OutlierAlgorithm

@Title(value="KNN outlier: Efficient Algorithms for Mining Outliers from Large Data Sets")
 @Description(value="Outlier Detection based on the distance of an object to its k nearest neighbor.")
 @Reference(authors="S. Ramaswamy, R. Rastogi, K. Shim",
           title="Efficient Algorithms for Mining Outliers from Large Data Sets",
           booktitle="Proc. Int. Conf. on Management of Data (SIGMOD 2000)",
           url="https://doi.org/10.1145/342009.335437",
           bibkey="DBLP:conf/sigmod/RamaswamyRS00")
 @Alias(value={"de.lmu.ifi.dbs.elki.algorithm.outlier.KNNOutlier","knno"})
 @Priority(value=200)
public class KNNOutlier<O>
extends AbstractDistanceBasedAlgorithm<O,OutlierResult>
implements OutlierAlgorithm

Outlier Detection based on the distance of an object to its k nearest neighbor.

This implementation differs from the original pseudocode: the k nearest neighbors do not exclude the point that is currently evaluated. I.e. for k=1 the resulting score is the distance to the 1-nearest neighbor that is not the query point and therefore should match k=2 in the exact pseudocode - a value of k=1 in the original code does not make sense, as the 1NN distance will be 0 for every point in the database. If you for any reason want to use the original algorithm, subtract 1 from the k parameter.

Reference:

S. Ramaswamy, R. Rastogi, K. Shim
Efficient Algorithms for Mining Outliers from Large Data Sets.
In: Proc. Int. Conf. on Management of Data (SIGMOD 2000)

Since:

0.3

Author:

Lisa Reichert

Nested Class Summary

Nested Classes

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

Field Summary

Fields

Modifier and Type	Field and Description
private int	k The parameter k (including query point!)
private static Logging	LOG The logger for this class.

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
KNNOutlier(DistanceFunction<? super O> distanceFunction, int k) Constructor for a single kNN query.

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) Runs the algorithm in the timed evaluation part.
OutlierResult	run(Relation<O> relation) Runs the algorithm in the timed evaluation part.

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

The logger for this class.

k

private int k

The parameter k (including query point!)

Constructor Detail

KNNOutlier

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

Constructor for a single kNN query.

Parameters:

distanceFunction - distance function to use

k - Value of k (excluding query point!)

Method Detail

run

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

Runs the algorithm in the timed evaluation part.

Parameters:

database - Database (no longer used)

relation - Data relation

run

public OutlierResult run(Relation<O> relation)

Runs the algorithm in the timed evaluation part.

Parameters:

relation - Data relation

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