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

Class CTLuGLSBackwardSearchAlgorithm<V extends NumberVector>

java.lang.Object

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

de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm<V,OutlierResult>

de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.CTLuGLSBackwardSearchAlgorithm<V>

Type Parameters:

V - Vector type to use for distances

All Implemented Interfaces:

Algorithm, DistanceBasedAlgorithm<V>, OutlierAlgorithm

@Title(value="GLS-Backward Search")
 @Reference(authors="F. Chen, C.-T. Lu, A. P. Boedihardjo",
           title="GLS-SOD: A Generalized Local Statistical Approach for Spatial Outlier Detection",
           booktitle="Proc. 16th ACM SIGKDD Int. Conf. Knowledge Discovery and Data Mining",
           url="https://doi.org/10.1145/1835804.1835939",
           bibkey="DBLP:conf/kdd/ChenLB10")
public class CTLuGLSBackwardSearchAlgorithm<V extends NumberVector>
extends AbstractDistanceBasedAlgorithm<V,OutlierResult>
implements OutlierAlgorithm

GLS-Backward Search is a statistical approach to detecting spatial outliers.

Implementation note: this is just the most basic version of this algorithm. The spatial relation must be two dimensional, the set of spatial basis functions is hard-coded (but trivial to enhance) to \(\{1,x,y,x^2,y^2,xy\}\), and we assume the neighborhood is large enough for the simpler formulas to work that make the optimization problem convex.

Reference:

F. Chen, C.-T. Lu, A. P. Boedihardjo
GLS-SOD: A Generalized Local Statistical Approach for Spatial Outlier Detection
Proc. 16th ACM SIGKDD Int. Conf. Knowledge Discovery and Data Mining

Since:

0.4.0

Author:

Ahmed Hettab

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	CTLuGLSBackwardSearchAlgorithm.Parameterizer<V extends NumberVector> Parameterization class

Field Summary

Fields

Modifier and Type	Field and Description
private double	alpha Parameter Alpha - significance niveau
private int	k Parameter k - neighborhood size
private static Logging	LOG The logger for this class.

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

ALGORITHM_ID

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

DISTANCE_FUNCTION_ID

Constructor Summary

Constructors

Constructor and Description
CTLuGLSBackwardSearchAlgorithm(DistanceFunction<? super V> distanceFunction, int k, double alpha) Constructor.

Method Summary

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<V> relationx, Relation<? extends NumberVector> relationy) Run the algorithm
private Pair<DBIDVar,java.lang.Double>	singleIteration(Relation<V> relationx, Relation<? extends NumberVector> relationy) Run a single iteration of the GLS-SOD modeling step

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

getDistanceFunction

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

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.

alpha

private double alpha

Parameter Alpha - significance niveau

k

private int k

Parameter k - neighborhood size

Constructor Detail

CTLuGLSBackwardSearchAlgorithm

public CTLuGLSBackwardSearchAlgorithm(DistanceFunction<? super V> distanceFunction,
                                      int k,
                                      double alpha)

Constructor.

Parameters:

distanceFunction - Distance function

k - number of nearest neighbors to use

alpha - Significance niveau

Method Detail

run

public OutlierResult run(Database database,
                         Relation<V> relationx,
                         Relation<? extends NumberVector> relationy)

Run the algorithm

Parameters:

database - Database to process

relationx - Spatial relation

relationy - Attribute relation

Returns:

Algorithm result

singleIteration

private Pair<DBIDVar,java.lang.Double> singleIteration(Relation<V> relationx,
                                                       Relation<? extends NumberVector> relationy)

Run a single iteration of the GLS-SOD modeling step

Parameters:

relationx - Geo relation

relationy - Attribute relation

Returns:

Top outlier and associated score

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