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

Class LDOF<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.lof.LDOF<O,D>

Type Parameters:

O - the type of DatabaseObjects handled by this Algorithm

All Implemented Interfaces:

Algorithm, DistanceBasedAlgorithm<O,D>, OutlierAlgorithm, Parameterizable

@Title(value="LDOF: Local Distance-Based Outlier Factor")
@Description(value="Local outlier detection appraoch suitable for scattered data by averaging the kNN distance over all k nearest neighbors")
@Reference(authors="K. Zhang, M. Hutter, H. Jin",
           title="A New Local Distance-Based Outlier Detection Approach for Scattered Real-World Data",
           booktitle="Proc. 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining (PAKDD 2009), Bangkok, Thailand, 2009",
           url="http://dx.doi.org/10.1007/978-3-642-01307-2_84")
@Alias(value="de.lmu.ifi.dbs.elki.algorithm.outlier.LDOF")
public class LDOF<O,D extends NumberDistance<D,?>>
extends AbstractDistanceBasedAlgorithm<O,D,OutlierResult>
implements OutlierAlgorithm

Computes the LDOF (Local Distance-Based Outlier Factor) for all objects of a Database.

Reference:
K. Zhang, M. Hutter, H. Jin: A New Local Distance-Based Outlier Detection Approach for Scattered Real-World Data.
In: Proc. 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining (PAKDD 2009), Bangkok, Thailand, 2009.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	LDOF.Parameterizer<O,D extends NumberDistance<D,?>> Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
(package private) int	k Holds the value of K_ID.
static OptionID	K_ID Parameter to specify the number of nearest neighbors of an object to be considered for computing its LDOF_SCORE, must be an integer greater than 1.
private static double	LDOF_BASELINE The baseline for LDOF values.
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
LDOF(DistanceFunction<? super O,D> distanceFunction, int k) Constructor.

Method Summary

Methods

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 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_ID

public static final OptionID K_ID

Parameter to specify the number of nearest neighbors of an object to be considered for computing its LDOF_SCORE, must be an integer greater than 1.

LDOF_BASELINE

private static final double LDOF_BASELINE

The baseline for LDOF values. The paper gives 0.5 for uniform distributions, although one might also discuss using 1.0 as baseline.

See Also:

Constant Field Values

k

int k

Holds the value of K_ID.

Constructor Detail

LDOF

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

Constructor.

Parameters:

distanceFunction - distance function

k - k Parameter

Method Detail

run

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

Run the algorithm

Parameters:

database - Database to process

relation - Relation to process

Returns:

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