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

Class ALOCI<O extends NumberVector<?>,D extends NumberDistance<D,?>>

java.lang.Object

de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm<OutlierResult>

de.lmu.ifi.dbs.elki.algorithm.outlier.ALOCI<O,D>

Type Parameters:

O - Object type

D - Distance type

All Implemented Interfaces:

Algorithm, OutlierAlgorithm, InspectionUtilFrequentlyScanned, Parameterizable

@Title(value="LOCI: Fast Outlier Detection Using the Local Correlation Integral")
@Description(value="Algorithm to compute outliers based on the Local Correlation Integral")
@Reference(authors="S. Papadimitriou, H. Kitagawa, P. B. Gibbons, C. Faloutsos",
           title="LOCI: Fast Outlier Detection Using the Local Correlation Integral",
           booktitle="Proc. 19th IEEE Int. Conf. on Data Engineering (ICDE \'03), Bangalore, India, 2003",
           url="http://dx.doi.org/10.1109/ICDE.2003.1260802")
public class ALOCI<O extends NumberVector<?>,D extends NumberDistance<D,?>>
extends AbstractAlgorithm<OutlierResult>
implements OutlierAlgorithm

Fast Outlier Detection Using the "approximate Local Correlation Integral". Outlier detection using multiple epsilon neighborhoods. Reference:

S. Papadimitriou, H. Kitagawa, P. B. Gibbons and C. Faloutsos:
LOCI: Fast Outlier Detection Using the Local Correlation Integral.
In: Proc. 19th IEEE Int. Conf. on Data Engineering (ICDE '03), Bangalore, India, 2003.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
(package private) static class	ALOCI.ALOCIQuadTree Simple quadtree for ALOCI.
(package private) static class	ALOCI.Node Node of the ALOCI Quadtree
static class	ALOCI.Parameterizer<O extends NumberVector<?>,D extends NumberDistance<D,?>> Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
private int	alpha Alpha (level difference of sampling and counting neighborhoods)
private NumberVectorDistanceFunction<D>	distFunc Distance function
private int	g Number of trees to generate (forest size)
private static Logging	LOG The logger for this class.
private int	nmin Minimum size for a leaf.
private RandomFactory	rnd Random generator

Constructor Summary

Constructors

Constructor and Description
ALOCI(NumberVectorDistanceFunction<D> distanceFunction, int nmin, int alpha, int g, RandomFactory rnd) Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
private static double	calculate_MDEF_norm(ALOCI.Node sn, ALOCI.Node cg) Method for the MDEF calculation
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)

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.

nmin

private int nmin

Minimum size for a leaf.

alpha

private int alpha

Alpha (level difference of sampling and counting neighborhoods)

g

private int g

Number of trees to generate (forest size)

rnd

private RandomFactory rnd

Random generator

distFunc

private NumberVectorDistanceFunction<D extends NumberDistance<D,?>> distFunc

Distance function

Constructor Detail

ALOCI

public ALOCI(NumberVectorDistanceFunction<D> distanceFunction,
     int nmin,
     int alpha,
     int g,
     RandomFactory rnd)

Constructor.

Parameters:

distanceFunction - Distance function

nmin - Minimum neighborhood size

alpha - Alpha value

g - Number of grids to use

rnd - Random generator.

Method Detail

run

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

calculate_MDEF_norm

private static double calculate_MDEF_norm(ALOCI.Node sn,
                         ALOCI.Node cg)

Method for the MDEF calculation

Parameters:

sn - Sampling Neighborhood

cg - Counting Neighborhood

Returns:

MDEF norm

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

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