de.lmu.ifi.dbs.elki.algorithm.outlier
Class LDOF<O extends DatabaseObject>

java.lang.Object
  de.lmu.ifi.dbs.elki.logging.AbstractLoggable
      de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm<O,R>
          de.lmu.ifi.dbs.elki.algorithm.DistanceBasedAlgorithm<O,DoubleDistance,OutlierResult>
              de.lmu.ifi.dbs.elki.algorithm.outlier.LDOF<O>

Type Parameters:

O - the type of DatabaseObjects handled by this Algorithm

All Implemented Interfaces:

Algorithm<O,OutlierResult>, 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")
public class LDOF<O extends DatabaseObject>
extends DistanceBasedAlgorithm<O,DoubleDistance,OutlierResult>

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.

Author:

Arthur Zimek

Field Summary

(package private) int	k Holds the value of K_PARAM.
static OptionID	K_ID OptionID for K_PARAM
private IntParameter	K_PARAM 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.
(package private) MaterializeKNNPreprocessor<O,DoubleDistance>	knnPreprocessor Preprocessor for materialization of kNN queries.
private static double	LDOF_BASELINE The baseline for LDOF values.
static AssociationID<Double>	LDOF_SCORE The association id to associate the LDOF_SCORE of an object for the LDOF algorithm.

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

DISTANCE_FUNCTION_ID, DISTANCE_FUNCTION_PARAM

Fields inherited from class de.lmu.ifi.dbs.elki.logging.AbstractLoggable

debug, logger

Constructor Summary

LDOF(Parameterization config)
Constructor, adhering to Parameterizable

Method Summary

protected OutlierResult

runInTime(Database<O> database) The run method encapsulated in measure of runtime.

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

getDistanceFactory, getDistanceFunction

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

isTime, isVerbose, run, setTime, setVerbose

Methods inherited from class de.lmu.ifi.dbs.elki.logging.AbstractLoggable

debugFine, debugFiner, debugFinest, exception, progress, verbose, warning

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

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

LDOF_SCORE

public static final AssociationID<Double> LDOF_SCORE

The association id to associate the LDOF_SCORE of an object for the LDOF algorithm.

K_ID

public static final OptionID K_ID

OptionID for K_PARAM

K_PARAM

private final IntParameter K_PARAM

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.

Key: -ldof.k

k

int k

Holds the value of K_PARAM.

knnPreprocessor

MaterializeKNNPreprocessor<O extends DatabaseObject,DoubleDistance> knnPreprocessor

Preprocessor for materialization of kNN queries.

Constructor Detail

LDOF

public LDOF(Parameterization config)

Constructor, adhering to Parameterizable

Parameters:

config - Parameterization

Method Detail

runInTime

protected OutlierResult runInTime(Database<O> database)
                           throws IllegalStateException

Description copied from class: AbstractAlgorithm

The run method encapsulated in measure of runtime. An extending class needs not to take care of runtime itself.

Specified by:

runInTime in class AbstractAlgorithm<O extends DatabaseObject,OutlierResult>

Parameters:

database - the database to run the algorithm on

Returns:

the Result computed by this algorithm

Throws:

IllegalStateException - if the algorithm has not been initialized properly (e.g. the setParameters(String[]) method has been failed to be called).