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

Class IDOS<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.intrinsic.IDOS<O>

Type Parameters:

O - Object type

All Implemented Interfaces:

Algorithm, DistanceBasedAlgorithm<O>, OutlierAlgorithm

@Reference(authors="Jonathan von Br\u00fcnken, Michael E. Houle, Arthur Zimek",
           title="Intrinsic Dimensional Outlier Detection in High-Dimensional Data",
           booktitle="NII Technical Report (NII-2015-003E)",
           url="http://www.nii.ac.jp/TechReports/15-003E.html")
public class IDOS<O>
extends AbstractDistanceBasedAlgorithm<O,OutlierResult>
implements OutlierAlgorithm

Intrinsic Dimensional Outlier Detection in High-Dimensional Data. Reference:

Jonathan von Brünken, Michael E. Houle, Arthur Zimek
Intrinsic Dimensional Outlier Detection in High-Dimensional Data
NII Technical Report (NII-2015-003E)

Author:

Jonathan von Brünken, Erich Schubert

Nested Class Summary

Nested Classes

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

Field Summary

Fields

Modifier and Type	Field and Description
protected IntrinsicDimensionalityEstimator	estimator Estimator for intrinsic dimensionality.
protected int	k_c kNN for the context set (ID computation).
protected int	k_r kNN for the reference set.
private static Logging	LOG The logger for this class.

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

DISTANCE_FUNCTION_ID

Constructor Summary

Constructors

Constructor and Description
IDOS(DistanceFunction<? super O> distanceFunction, IntrinsicDimensionalityEstimator estimator, int kc, int kr) Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
protected DoubleDataStore	computeIDOS(DBIDs ids, KNNQuery<O> knnQ, DoubleDataStore intDims, DoubleMinMax idosminmax) Computes all IDOS scores.
protected DoubleDataStore	computeIDs(DBIDs ids, KNNQuery<O> knnQ) Computes all IDs
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 algorithm

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

LOG

private static final Logging LOG

The logger for this class.

k_c

protected int k_c

kNN for the context set (ID computation).

k_r

protected int k_r

kNN for the reference set.

estimator

protected IntrinsicDimensionalityEstimator estimator

Estimator for intrinsic dimensionality.

Constructor Detail

IDOS

public IDOS(DistanceFunction<? super O> distanceFunction,
    IntrinsicDimensionalityEstimator estimator,
    int kc,
    int kr)

Constructor.

Parameters:

distanceFunction - the distance function to use

estimator - Estimator for intrinsic dimensionality

kc - the context set size for the ID computation

kr - the neighborhood size to use in score computation

Method Detail

run

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

Run the algorithm

Parameters:

database - Database

relation - Data relation

Returns:

Outlier result

computeIDs

protected DoubleDataStore computeIDs(DBIDs ids,
                         KNNQuery<O> knnQ)

Computes all IDs

Parameters:

ids - the DBIDs to process

knnQ - the KNN query

Returns:

The computed intrinsic dimensionalities.

computeIDOS

protected DoubleDataStore computeIDOS(DBIDs ids,
                          KNNQuery<O> knnQ,
                          DoubleDataStore intDims,
                          DoubleMinMax idosminmax)

Computes all IDOS scores.

Parameters:

ids - the DBIDs to process

knnQ - the KNN query

intDims - Precomputed intrinsic dimensionalities

idosminmax - Output of minimum and maximum, for metadata

Returns:

ID scores

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