Package org.deidentifier.arx.metric.v2
Klasse MetricMDStatic
java.lang.Object
org.deidentifier.arx.metric.Metric<AbstractILMultiDimensional>
org.deidentifier.arx.metric.v2.AbstractMetricMultiDimensional
org.deidentifier.arx.metric.v2.MetricMDStatic
- Alle implementierten Schnittstellen:
Serializable
This class provides an implementation of a static metric in
which information loss is user-defined per generalization level.
This metric will respect attribute weights defined in the configuration.
TODO: Add reference
- Siehe auch:
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Verschachtelte Klassen - Übersicht
Von Klasse geerbte verschachtelte Klassen/Schnittstellen org.deidentifier.arx.metric.Metric
Metric.AggregateFunction -
Methodenübersicht
Modifizierer und TypMethodeBeschreibungReturns the configuration of this metric.render(ARXConfiguration config) Renders the privacy modeltoString()Returns the name of metric.Von Klasse geerbte Methoden org.deidentifier.arx.metric.v2.AbstractMetricMultiDimensional
createMaxInformationLoss, createMinInformationLoss, getAggregateFunctionVon Klasse geerbte Methoden org.deidentifier.arx.metric.Metric
createAECSMetric, createAECSMetric, createAmbiguityMetric, createClassificationMetric, createClassificationMetric, createDiscernabilityMetric, createDiscernabilityMetric, createEntropyBasedInformationLossMetric, createEntropyBasedInformationLossMetric, createEntropyMetric, createEntropyMetric, createEntropyMetric, createEntropyMetric, createEntropyMetric, createEntropyMetric, createHeightMetric, createHeightMetric, createInstanceOfHighestScore, createInstanceOfLowestScore, createKLDivergenceMetric, createLossMetric, createLossMetric, createLossMetric, createLossMetric, createMetric, createNormalizedEntropyMetric, createNormalizedEntropyMetric, createPrecisionMetric, createPrecisionMetric, createPrecisionMetric, createPrecisionMetric, createPrecisionMetric, createPrecisionMetric, createPrecisionMetric, createPrecisionMetric, createPrecomputedEntropyMetric, createPrecomputedEntropyMetric, createPrecomputedEntropyMetric, createPrecomputedEntropyMetric, createPrecomputedEntropyMetric, createPrecomputedEntropyMetric, createPrecomputedLossMetric, createPrecomputedLossMetric, createPrecomputedLossMetric, createPrecomputedLossMetric, createPrecomputedNormalizedEntropyMetric, createPrecomputedNormalizedEntropyMetric, createPublisherPayoutMetric, createPublisherPayoutMetric, createStaticMetric, createStaticMetric, getDescription, getGeneralizationFactor, getGeneralizationSuppressionFactor, getInformationLoss, getInformationLoss, getLowerBound, getLowerBound, getName, getScore, getSuppressionFactor, initialize, isAbleToHandleClusteredMicroaggregation, isAbleToHandleMicroaggregation, isGSFactorSupported, isIndependent, isMonotonic, isMonotonicWithGeneralization, isMonotonicWithSuppression, isMultiDimensional, isPrecomputed, isScoreFunctionSupported, isWeighted, list
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Methodendetails
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getConfiguration
Returns the configuration of this metric.- Setzt außer Kraft:
getConfigurationin KlasseMetric<AbstractILMultiDimensional>- Gibt zurück:
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render
Beschreibung aus Klasse kopiert:MetricRenders the privacy model- Angegeben von:
renderin KlasseMetric<AbstractILMultiDimensional>- Gibt zurück:
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toString
Beschreibung aus Klasse kopiert:MetricReturns the name of metric.- Setzt außer Kraft:
toStringin KlasseMetric<AbstractILMultiDimensional>- Gibt zurück:
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