Package elki.outlier.spatial
Class TrimmedMeanApproach<N>
- java.lang.Object
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- elki.outlier.spatial.AbstractNeighborhoodOutlier<N>
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- elki.outlier.spatial.TrimmedMeanApproach<N>
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- 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 8the 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
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Nested Class Summary
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Nested classes/interfaces inherited from interface elki.Algorithm
Algorithm.Utils
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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
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Constructor Summary
Constructors Constructor Description TrimmedMeanApproach(NeighborSetPredicate.Factory<N> npredf, double p)
Constructor.
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Method Summary
All Methods Instance Methods Concrete Methods 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
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Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
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Methods inherited from interface elki.outlier.OutlierAlgorithm
autorun
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Field Detail
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LOG
private static final Logging LOG
The logger for this class.
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p
private double p
the parameter p.
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Constructor Detail
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TrimmedMeanApproach
public TrimmedMeanApproach(NeighborSetPredicate.Factory<N> npredf, double p)
Constructor.- Parameters:
p
- Parameter pnpredf
- Neighborhood factory.
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Method Detail
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getInputTypeRestriction
public TypeInformation[] getInputTypeRestriction()
Description copied from interface:Algorithm
Get the input type restriction used for negotiating the data query.- Returns:
- Type restriction
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run
public OutlierResult run(Database database, Relation<N> nrel, Relation<? extends NumberVector> relation)
Run the algorithm.- Parameters:
database
- Databasenrel
- Neighborhood relationrelation
- Data Relation (1 dimensional!)- Returns:
- Outlier detection result
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