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

Class LOCI<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.LOCI<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 LOCI<O,D extends NumberDistance<D,?>>
extends AbstractDistanceBasedAlgorithm<O,D,OutlierResult>
implements OutlierAlgorithm

Fast Outlier Detection Using the "Local Correlation Integral". Exact implementation only, not aLOCI. TODO: add aLOCI Outlier detection using multiple epsilon neighborhoods. Based on: 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
static class	LOCI.Parameterizer<O,D extends NumberDistance<D,?>> Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
private double	alpha Holds the value of ALPHA_ID.
static OptionID	ALPHA_ID Parameter to specify the averaging neighborhood scaling.
private static Logging	logger The logger for this class.
private int	nmin Holds the value of NMIN_ID.
static OptionID	NMIN_ID Parameter to specify the minimum neighborhood size
private D	rmax Holds the value of RMAX_ID.
static OptionID	RMAX_ID Parameter to specify the maximum radius of the neighborhood to be considered, must be suitable to the distance function specified.

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

DISTANCE_FUNCTION_ID

Constructor Summary

Constructors

Constructor and Description
LOCI(DistanceFunction<? super O,D> distanceFunction, D rmax, int nmin, double alpha) 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) 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

Methods inherited from class java.lang.Object

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

Field Detail

logger

private static final Logging logger

The logger for this class.

RMAX_ID

public static final OptionID RMAX_ID

Parameter to specify the maximum radius of the neighborhood to be considered, must be suitable to the distance function specified.

NMIN_ID

public static final OptionID NMIN_ID

Parameter to specify the minimum neighborhood size

ALPHA_ID

public static final OptionID ALPHA_ID

Parameter to specify the averaging neighborhood scaling.

rmax

private D extends NumberDistance<D,?> rmax

Holds the value of RMAX_ID.

nmin

private int nmin

Holds the value of NMIN_ID.

alpha

private double alpha

Holds the value of ALPHA_ID.

Constructor Detail

LOCI

public LOCI(DistanceFunction<? super O,D> distanceFunction,
    D rmax,
    int nmin,
    double alpha)

Constructor.

Parameters:

distanceFunction - Distance function

rmax - Maximum radius

nmin - Minimum neighborhood size

alpha - Alpha value

Method Detail

run

public OutlierResult run(Database database)
                  throws IllegalStateException

Runs the algorithm in the timed evaluation part.

Specified by:

run in interface Algorithm

Specified by:

run in interface OutlierAlgorithm

Overrides:

run in class AbstractAlgorithm<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).

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