de.lmu.ifi.dbs.elki.algorithm.outlier
Class SOD<V extends NumberVector<V,?>>

java.lang.Object
  de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm<OutlierResult>
      de.lmu.ifi.dbs.elki.algorithm.outlier.SOD<V>

Type Parameters:

V - the type of NumberVector handled by this Algorithm

All Implemented Interfaces:

Algorithm, OutlierAlgorithm, InspectionUtilFrequentlyScanned, Parameterizable

@Title(value="SOD: Subspace outlier degree")
@Description(value="Outlier Detection in Axis-Parallel Subspaces of High Dimensional Data")
@Reference(authors="H.-P. Kriegel, P. Kr\u00f6ger, E. Schubert, A. Zimek",
           title="Outlier Detection in Axis-Parallel Subspaces of High Dimensional Data",
           booktitle="Proceedings of the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Bangkok, Thailand, 2009",
           url="http://dx.doi.org/10.1007/978-3-642-01307-2")
public class SOD<V extends NumberVector<V,?>>
extends AbstractAlgorithm<OutlierResult>
implements OutlierAlgorithm

Nested Class Summary

static class	SOD.Parameterizer<V extends NumberVector<V,?>> Parameterization class.
static class	SOD.SODModel<O extends NumberVector<O,?>>
protected static class	SOD.SODProxyScoreResult Proxy class that converts a model result to an actual SOD score result.

Field Summary

private double	alpha Holds the value of ALPHA_ID.
static OptionID	ALPHA_ID Parameter to indicate the multiplier for the discriminance value for discerning small from large variances.
private int	knn Holds the value of KNN_ID.
static OptionID	KNN_ID Parameter to specify the number of shared nearest neighbors to be considered for learning the subspace properties., must be an integer greater than 0.
private static Logging	logger The logger for this class.
private SharedNearestNeighborSimilarityFunction<V>	similarityFunction The similarity function.

Constructor Summary

SOD(int knn, double alpha, SharedNearestNeighborSimilarityFunction<V> similarityFunction)
Constructor with parameters.

Method Summary

TypeInformation[]	getInputTypeRestriction() Get the input type restriction used for negotiating the data query.
private KNNList<DoubleDistance>	getKNN(Relation<V> database, SimilarityQuery<V,IntegerDistance> snnInstance, DBID queryObject) Provides the k nearest neighbors in terms of the shared nearest neighbor distance.
protected Logging	getLogger() Get the (STATIC) logger for this class.
OutlierResult	run(Relation<V> relation) Performs the SOD algorithm on the given database.

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.

KNN_ID

public static final OptionID KNN_ID

Parameter to specify the number of shared nearest neighbors to be considered for learning the subspace properties., must be an integer greater than 0.

ALPHA_ID

public static final OptionID ALPHA_ID

Parameter to indicate the multiplier for the discriminance value for discerning small from large variances.

knn

private int knn

Holds the value of KNN_ID.

alpha

private double alpha

Holds the value of ALPHA_ID.

similarityFunction

private SharedNearestNeighborSimilarityFunction<V extends NumberVector<V,?>> similarityFunction

The similarity function.

Constructor Detail

SOD

public SOD(int knn,
           double alpha,
           SharedNearestNeighborSimilarityFunction<V> similarityFunction)

Constructor with parameters.

Parameters:

knn - knn value

alpha - Alpha parameter

similarityFunction - Shared nearest neighbor similarity function

Method Detail

run

public OutlierResult run(Relation<V> relation)
                  throws IllegalStateException

Performs the SOD algorithm on the given database.

Parameters:

relation - Data relation to process

Throws:

IllegalStateException

getKNN

private KNNList<DoubleDistance> getKNN(Relation<V> database,
                                       SimilarityQuery<V,IntegerDistance> snnInstance,
                                       DBID queryObject)

Provides the k nearest neighbors in terms of the shared nearest neighbor distance.

The query object is excluded from the knn list.

Parameters:

database - the database holding the objects

snnInstance - similarity function

queryObject - the query object for which the kNNs should be determined

Returns:

the k nearest neighbors in terms of the shared nearest neighbor distance without the query object

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