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

Class CTLuGLSBackwardSearchAlgorithm<V extends NumberVector<?>,D extends NumberDistance<D,?>>

java.lang.Object

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

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

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

Type Parameters:

V - Vector type to use for distances

D - Distance function to use

All Implemented Interfaces:

Algorithm, DistanceBasedAlgorithm<V,D>, OutlierAlgorithm, Parameterizable

@Title(value="GLS-Backward Search")
@Reference(authors="F. Chen and C.-T. Lu and A. P. Boedihardjo",
           title="GLS-SOD: A Generalized Local Statistical Approach for Spatial Outlier Detection",
           booktitle="Proc. 16th ACM SIGKDD international conference on Knowledge discovery and data mining",
           url="http://dx.doi.org/10.1145/1835804.1835939")
public class CTLuGLSBackwardSearchAlgorithm<V extends NumberVector<?>,D extends NumberDistance<D,?>>
extends AbstractDistanceBasedAlgorithm<V,D,OutlierResult>
implements OutlierAlgorithm

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

F. Chen and C.-T. Lu and A. P. Boedihardjo:
GLS-SOD: A Generalized Local Statistical Approach for Spatial Outlier Detection
In Proc. 16th ACM SIGKDD international conference on Knowledge discovery and data mining, 2010

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*x,y*y,x*y}, and we assume the neighborhood is large enough for the simpler formulas to work that make the optimization problem convex.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	CTLuGLSBackwardSearchAlgorithm.Parameterizer<V extends NumberVector<?>,D extends NumberDistance<D,?>> 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 interface de.lmu.ifi.dbs.elki.algorithm.DistanceBasedAlgorithm

DISTANCE_FUNCTION_ID

Constructor Summary

Constructors

Constructor and Description
CTLuGLSBackwardSearchAlgorithm(DistanceFunction<V,D> distanceFunction, int k, 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, Relation<V> relationx, Relation<? extends NumberVector<?>> relationy) Run the algorithm
private Pair<DBIDVar,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

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.

alpha

private double alpha

Parameter Alpha - significance niveau

k

private int k

Parameter k - neighborhood size

Constructor Detail

CTLuGLSBackwardSearchAlgorithm

public CTLuGLSBackwardSearchAlgorithm(DistanceFunction<V,D> 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,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