Package org.deidentifier.arx.metric
Klasse MetricNMEntropy
java.lang.Object
org.deidentifier.arx.metric.Metric<org.deidentifier.arx.metric.InformationLossDefault>
org.deidentifier.arx.metric.MetricDefault
org.deidentifier.arx.metric.MetricEntropy
org.deidentifier.arx.metric.MetricNMEntropy
- Alle implementierten Schnittstellen:
Serializable
This class provides an efficient implementation of a non-monotonic and
non-uniform entropy metric. It avoids a cell-by-cell process by utilizing a
three-dimensional array that maps identifiers to their frequency for all
quasi-identifiers and generalization levels. It further reduces the overhead
induced by subsequent calls by caching the results for previous columns and
generalization levels. It takes supressed tuples into account by adding the
information loss induced by suppressing the transformed representation of the
outliers.
- Siehe auch:
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Verschachtelte Klassen - Übersicht
Von Klasse geerbte verschachtelte Klassen/Schnittstellen org.deidentifier.arx.metric.Metric
Metric.AggregateFunction -
Konstruktorübersicht
Konstruktoren -
Methodenübersicht
Modifizierer und TypMethodeBeschreibungprotected InformationLossWithBound<org.deidentifier.arx.metric.InformationLossDefault> getInformationLossInternal(Transformation<?> node, HashGroupify g) Evaluates the metric for the given node.protected org.deidentifier.arx.metric.InformationLossDefaultgetLowerBoundInternal(Transformation<?> node) Returns a lower bound for the information loss for the given node.protected org.deidentifier.arx.metric.InformationLossDefaultgetLowerBoundInternal(Transformation<?> node, HashGroupify groupify) Returns a lower bound for the information loss for the given node.protected voidinitializeInternal(DataManager manager, DataDefinition definition, Data input, GeneralizationHierarchy[] hierarchies, ARXConfiguration config) Implement this to initialize the metric.render(ARXConfiguration config) Renders the privacy modeltoString()Returns the name of metric.Von Klasse geerbte Methoden org.deidentifier.arx.metric.MetricEntropy
getCache, getCardinalities, getHierarchies, getInformationLossInternalVon Klasse geerbte Methoden org.deidentifier.arx.metric.MetricDefault
createMaxInformationLoss, createMinInformationLossVon 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, getAggregateFunction, getConfiguration, getDescription, getDescription, getGeneralizationFactor, getGeneralizationSuppressionFactor, getInformationLoss, getInformationLoss, getLowerBound, getLowerBound, getName, getNumRecords, getScore, getSubset, getSuppressionFactor, initialize, isAbleToHandleClusteredMicroaggregation, isAbleToHandleMicroaggregation, isGSFactorSupported, isIndependent, isMonotonic, isMonotonicWithGeneralization, isMonotonicWithSuppression, isMultiDimensional, isPrecomputed, isScoreFunctionSupported, isWeighted, list, round
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Konstruktordetails
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MetricNMEntropy
protected MetricNMEntropy()Creates a new instance.
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Methodendetails
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render
Beschreibung aus Klasse kopiert:MetricRenders the privacy model- Setzt außer Kraft:
renderin KlasseMetricEntropy- Gibt zurück:
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toString
Beschreibung aus Klasse kopiert:MetricReturns the name of metric.- Setzt außer Kraft:
toStringin KlasseMetricEntropy- Gibt zurück:
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getInformationLossInternal
protected InformationLossWithBound<org.deidentifier.arx.metric.InformationLossDefault> getInformationLossInternal(Transformation<?> node, HashGroupify g) Beschreibung aus Klasse kopiert:MetricEvaluates the metric for the given node.- Setzt außer Kraft:
getInformationLossInternalin KlasseMetricEntropy- Parameter:
node- The node for which to compute the information lossg- The groupify operator of the previous check- Gibt zurück:
- the double
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getLowerBoundInternal
protected org.deidentifier.arx.metric.InformationLossDefault getLowerBoundInternal(Transformation<?> node) Beschreibung aus Klasse kopiert:MetricReturns a lower bound for the information loss for the given node. This can be used to expose the results of monotonic shares of a metric, which can significantly speed-up the anonymization process. If no such metric exists, simply returnnull.- Setzt außer Kraft:
getLowerBoundInternalin KlasseMetricEntropy- Parameter:
node-- Gibt zurück:
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getLowerBoundInternal
protected org.deidentifier.arx.metric.InformationLossDefault getLowerBoundInternal(Transformation<?> node, HashGroupify groupify) Beschreibung aus Klasse kopiert:MetricReturns a lower bound for the information loss for the given node. This can be used to expose the results of monotonic shares of a metric, which can significantly speed-up the anonymization process. If no such metric exists, simply returnnull.
This variant of the method allows computing a monotonic share based on a groupified data representation. IMPORTANT NOTE: The groups may not have been classified correctly when the method is called, i.e., HashGroupifyEntry.isNotOutlier may not be set correctly!- Setzt außer Kraft:
getLowerBoundInternalin KlasseMetricEntropy- Parameter:
node-groupify-- Gibt zurück:
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initializeInternal
protected void initializeInternal(DataManager manager, DataDefinition definition, Data input, GeneralizationHierarchy[] hierarchies, ARXConfiguration config) Beschreibung aus Klasse kopiert:MetricImplement this to initialize the metric.- Setzt außer Kraft:
initializeInternalin KlasseMetricEntropy- Parameter:
manager-definition-input-hierarchies-config-
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