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

Class LocalIsolationCoefficient<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.distance.LocalIsolationCoefficient<O>

Type Parameters:

O - the type of objects handled by this Algorithm

All Implemented Interfaces:

Algorithm, DistanceBasedAlgorithm<O>, OutlierAlgorithm

@Reference(authors="B. Yu, and M. Song, and L. Wang",
           title="Local Isolation Coefficient-Based Outlier Mining Algorithm",
           booktitle="Int. Conf. on Information Technology and Computer Science (ITCS) 2009",
           url="http://dx.doi.org/10.1109/ITCS.2009.230")
public class LocalIsolationCoefficient<O>
extends AbstractDistanceBasedAlgorithm<O,OutlierResult>
implements OutlierAlgorithm

The Local Isolation Coefficient is the sum of the kNN distance and the average distance to its k nearest neighbors. The algorithm originally used a normalized Manhattan distance on numerical attributes, and Hamming distance on categorial attributes. Reference:

B. Yu, and M. Song, and L. Wang
Local Isolation Coefficient-Based Outlier Mining Algorithm
Int. Conf. on Information Technology and Computer Science (ITCS) 2009

Author:

Erich Schubert

Nested Class Summary

Nested Classes

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

Field Summary

Fields

Modifier and Type	Field and Description
private int	k Holds the number of nearest neighbors to query (including query point!)
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
LocalIsolationCoefficient(DistanceFunction<? super O> distanceFunction, int k) Constructor with parameters.

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) 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

LOG

private static final Logging LOG

The logger for this class.

k

private int k

Holds the number of nearest neighbors to query (including query point!)

Constructor Detail

LocalIsolationCoefficient

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

Constructor with parameters.

Parameters:

distanceFunction - Distance function

k - k Parameter (not including query point!)

Method Detail

run

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

Runs the algorithm in the timed evaluation part.

Parameters:

database - Database context

relation - Data relation

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