de.lmu.ifi.dbs.elki.algorithm.outlier
Class KNNOutlier<O,D extends NumberDistance<D,?>>

java.lang.Object
  de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm<R>
      de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm<O,D,OutlierResult>
          de.lmu.ifi.dbs.elki.algorithm.outlier.KNNOutlier<O,D>

Type Parameters:

O - the type of DatabaseObjects handled by this Algorithm

D - the type of Distance used by this Algorithm

All Implemented Interfaces:

Algorithm, OutlierAlgorithm, InspectionUtilFrequentlyScanned, Parameterizable

@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. of the Int. Conf. on Management of Data, Dallas, Texas, 2000",
           url="http://dx.doi.org/10.1145/342009.335437")
public class KNNOutlier<O,D extends NumberDistance<D,?>>
extends AbstractDistanceBasedAlgorithm<O,D,OutlierResult>
implements OutlierAlgorithm

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

Reference:
S. Ramaswamy, R. Rastogi, K. Shim: Efficient Algorithms for Mining Outliers from Large Data Sets.
In: Proc. of the Int. Conf. on Management of Data, Dallas, Texas, 2000.

Nested Class Summary

static class

KNNOutlier.Parameterizer<O,D extends NumberDistance<D,?>> Parameterization class.

Field Summary

private int	k The parameter k
static OptionID	K_ID Parameter to specify the k nearest neighbor
private static Logging	logger The logger for this class.

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

DISTANCE_FUNCTION_ID

Constructor Summary

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

Method Summary

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.

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

getDistanceFunction

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

makeParameterDistanceFunction, 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

logger

private static final Logging logger

The logger for this class.

K_ID

public static final OptionID K_ID

Parameter to specify the k nearest neighbor

k

private int k

The parameter k

Constructor Detail

KNNOutlier

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

Constructor for a single kNN query.

Parameters:

distanceFunction - distance function to use

k - Value of k

Method Detail

run

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

Runs the algorithm in the timed evaluation part.

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