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, OutlierAlgorithm, InspectionUtilFrequentlyScanned, 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

static class

CTLuGLSBackwardSearchAlgorithm.Parameterizer<V extends NumberVector<?,?>,D extends NumberDistance<D,?>> Parameterization class

Field Summary

private double	alpha Parameter Alpha - significance niveau
private int	k Parameter k - neighborhood size
private static Logging	logger The logger for this class.

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

DISTANCE_FUNCTION_ID

Constructor Summary

CTLuGLSBackwardSearchAlgorithm(DistanceFunction<V,D> distanceFunction, int k, double alpha)
Constructor.

Method Summary

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(Relation<V> relationx, Relation<? extends NumberVector<?,?>> relationy) Run the algorithm
private Pair<DBID,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

logger

private static final Logging logger

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(Relation<V> relationx,
                         Relation<? extends NumberVector<?,?>> relationy)

Run the algorithm

Parameters:

relationx - Spatial relation

relationy - Attribute relation

Returns:

Algorithm result

singleIteration

private Pair<DBID,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