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

Class CTLuMeanMultipleAttributes<N,O extends NumberVector<?,?>>

java.lang.Object

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

de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.AbstractNeighborhoodOutlier<N>

de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.CTLuMeanMultipleAttributes<N,O>

Type Parameters:

N - Spatial Vector

O - Attribute Vector

All Implemented Interfaces:

Algorithm, OutlierAlgorithm, InspectionUtilFrequentlyScanned, Parameterizable

@Reference(authors="Chang-Tien Lu and Dechang Chen and Yufeng Kou",
           title="Detecting Spatial Outliers with Multiple Attributes",
           booktitle="Proc. 15th IEEE International Conference on Tools with Artificial Intelligence, 2003",
           url="http://dx.doi.org/10.1109/TAI.2003.1250179")
public class CTLuMeanMultipleAttributes<N,O extends NumberVector<?,?>>
extends AbstractNeighborhoodOutlier<N>

Mean Approach is used to discover spatial outliers with multiple attributes.

Reference:
Chang-Tien Lu and Dechang Chen and Yufeng Kou:
Detecting Spatial Outliers with Multiple Attributes
in 15th IEEE International Conference on Tools with Artificial Intelligence, 2003

Implementation note: attribute standardization is not used; this is equivalent to using the AttributeWiseVarianceNormalization filter.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	CTLuMeanMultipleAttributes.Parameterizer<N,O extends NumberVector<?,?>> Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
static Logging	logger logger

Fields inherited from class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.AbstractNeighborhoodOutlier

NEIGHBORHOOD_ID

Constructor Summary

Constructors

Constructor and Description
CTLuMeanMultipleAttributes(NeighborSetPredicate.Factory<N> npredf) 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(Relation<N> spatial, Relation<O> attributes)

Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.AbstractNeighborhoodOutlier

getNeighborSetPredicateFactory

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

public static final Logging logger

logger

Constructor Detail

CTLuMeanMultipleAttributes

public CTLuMeanMultipleAttributes(NeighborSetPredicate.Factory<N> npredf)

Constructor

Parameters:

npredf - Neighborhood predicate

Method Detail

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

run

public OutlierResult run(Relation<N> spatial,
                Relation<O> attributes)

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