Package elki.outlier.spatial

Class TrimmedMeanApproach<N>

java.lang.Object

elki.outlier.spatial.AbstractNeighborhoodOutlier<N>

elki.outlier.spatial.TrimmedMeanApproach<N>

Type Parameters:

N - Neighborhood object type

All Implemented Interfaces:

Algorithm, OutlierAlgorithm

@Title("A Trimmed Mean Approach to Finding Spatial Outliers")
@Description("A local trimmed mean approach to evaluating the spatial outlier factor which is the degree that a site is outlying compared to its neighbors")
@Reference(authors="T. Hu, S. Y. Sung",
           title="A trimmed mean approach to finding spatial outliers",
           booktitle="Intelligent Data Analysis 8",
           url="http://content.iospress.com/articles/intelligent-data-analysis/ida00153",
           bibkey="DBLP:journals/ida/HuS04")
public class TrimmedMeanApproach<N>
extends AbstractNeighborhoodOutlier<N>

A Trimmed Mean Approach to Finding Spatial Outliers.

Outliers are defined by their value deviation from a trimmed mean of the neighbors.

Reference:

T. Hu, S. Y. Sung
A Trimmed Mean Approach to finding Spatial Outliers
Intelligent Data Analysis 8

the contiguity Matrix is definit as
wij = 1/k if j is neighbor of i, k is the neighbors size of i.

Since:

0.4.0

Author:

Ahmed Hettab

Nested Class Summary

Nested classes/interfaces inherited from interface elki.Algorithm

Algorithm.Utils

Field Summary

Fields

Modifier and Type	Field	Description
private static Logging	LOG	The logger for this class.
private double	p	the parameter p.

Fields inherited from class elki.outlier.spatial.AbstractNeighborhoodOutlier

NEIGHBORHOOD_ID

Constructor Summary

Constructors

Constructor	Description
TrimmedMeanApproach(NeighborSetPredicate.Factory<N> npredf, double p)	Constructor.

Method Summary

Modifier and Type	Method	Description
TypeInformation[]	getInputTypeRestriction()	Get the input type restriction used for negotiating the data query.
OutlierResult	run(Database database, Relation<N> nrel, Relation<? extends NumberVector> relation)	Run the algorithm.

Methods inherited from class elki.outlier.spatial.AbstractNeighborhoodOutlier

getNeighborSetPredicateFactory

Methods inherited from class java.lang.Object

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

Methods inherited from interface elki.outlier.OutlierAlgorithm

autorun

Field Detail

LOG

private static final Logging LOG

The logger for this class.

p

private double p

the parameter p.

Constructor Detail

TrimmedMeanApproach

public TrimmedMeanApproach(NeighborSetPredicate.Factory<N> npredf,
                           double p)

Constructor.

Parameters:

p - Parameter p

npredf - Neighborhood factory.

Method Detail

getInputTypeRestriction

public TypeInformation[] getInputTypeRestriction()

Description copied from interface: Algorithm

Get the input type restriction used for negotiating the data query.

Returns:

Type restriction

run

public OutlierResult run(Database database,
                         Relation<N> nrel,
                         Relation<? extends NumberVector> relation)

Run the algorithm.

Parameters:

database - Database

nrel - Neighborhood relation

relation - Data Relation (1 dimensional!)

Returns:

Outlier detection result