O
- Data typepublic class EstimateIntrinsicDimensionality<O> extends AbstractDistanceBasedAlgorithm<O,Result>
Modifier and Type | Class and Description |
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static class |
EstimateIntrinsicDimensionality.Parameterizer<O>
Parameterization class.
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Modifier and Type | Field and Description |
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private IntrinsicDimensionalityEstimator |
estimator
Estimation method.
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private double |
krate
Number of neighbors to use.
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private static Logging |
LOG
Class logger.
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private double |
samples
Number of samples to draw.
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DISTANCE_FUNCTION_ID
Constructor and Description |
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EstimateIntrinsicDimensionality(DistanceFunction<? super O> distanceFunction,
IntrinsicDimensionalityEstimator estimator,
double krate,
double samples)
Constructor.
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Modifier and Type | Method and Description |
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TypeInformation[] |
getInputTypeRestriction()
Get the input type restriction used for negotiating the data query.
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protected Logging |
getLogger()
Get the (STATIC) logger for this class.
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Result |
run(Database database,
Relation<O> relation) |
getDistanceFunction
makeParameterDistanceFunction, run
private static final Logging LOG
private double krate
private double samples
private IntrinsicDimensionalityEstimator estimator
public EstimateIntrinsicDimensionality(DistanceFunction<? super O> distanceFunction, IntrinsicDimensionalityEstimator estimator, double krate, double samples)
distanceFunction
- Distance functionestimator
- Estimatorkrate
- kNN ratesamples
- Sample sizepublic TypeInformation[] getInputTypeRestriction()
AbstractAlgorithm
getInputTypeRestriction
in interface Algorithm
getInputTypeRestriction
in class AbstractAlgorithm<Result>
protected Logging getLogger()
AbstractAlgorithm
getLogger
in class AbstractAlgorithm<Result>
Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.