Package org.deidentifier.arx.metric.v2
Klasse MetricMDNUNMNormalizedEntropyPrecomputed
java.lang.Object
org.deidentifier.arx.metric.Metric<AbstractILMultiDimensional>
org.deidentifier.arx.metric.v2.AbstractMetricMultiDimensional
org.deidentifier.arx.metric.v2.MetricMDNUEntropyPrecomputed
org.deidentifier.arx.metric.v2.MetricMDNUNMEntropyPrecomputed
org.deidentifier.arx.metric.v2.MetricMDNUNMNormalizedEntropyPrecomputed
- Alle implementierten Schnittstellen:
Serializable
- Bekannte direkte Unterklassen:
MetricMDNUNMNormalizedEntropy
This class provides an efficient implementation of normalized non-uniform entropy. See:
A. De Waal and L. Willenborg: "Information loss through global recoding and local suppression" Netherlands Off Stat, vol. 14, pp. 17–20, 1999.
A. De Waal and L. Willenborg: "Information loss through global recoding and local suppression" Netherlands Off Stat, vol. 14, pp. 17–20, 1999.
- Siehe auch:
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Verschachtelte Klassen - Übersicht
Von Klasse geerbte verschachtelte Klassen/Schnittstellen org.deidentifier.arx.metric.Metric
Metric.AggregateFunction -
Feldübersicht
Von Klasse geerbte Felder org.deidentifier.arx.metric.v2.AbstractMetricMultiDimensional
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Konstruktorübersicht
KonstruktorenModifiziererKonstruktorBeschreibungprotectedCreates a new instance.Creates a new instance. -
Methodenübersicht
Modifizierer und TypMethodeBeschreibungReturns the configuration of this metric.protected ILMultiDimensionalWithBoundgetInformationLossInternal(org.deidentifier.arx.framework.lattice.Transformation<?> node, org.deidentifier.arx.framework.check.groupify.HashGroupify g) Evaluates the metric for the given node.protected ILMultiDimensionalWithBoundgetInformationLossInternal(org.deidentifier.arx.framework.lattice.Transformation<?> node, org.deidentifier.arx.framework.check.groupify.HashGroupifyEntry entry) Returns the information loss that would be induced by suppressing the given entry.protected AbstractILMultiDimensionalgetLowerBoundInternal(org.deidentifier.arx.framework.lattice.Transformation<?> node) Returns a lower bound for the information loss for the given node.protected AbstractILMultiDimensionalgetLowerBoundInternal(org.deidentifier.arx.framework.lattice.Transformation<?> node, org.deidentifier.arx.framework.check.groupify.HashGroupify groupify) Returns a lower bound for the information loss for the given node.getName()Returns the name of metric.protected voidinitializeInternal(org.deidentifier.arx.framework.data.DataManager manager, DataDefinition definition, org.deidentifier.arx.framework.data.Data input, org.deidentifier.arx.framework.data.GeneralizationHierarchy[] hierarchies, ARXConfiguration config) Implement this to initialize the metric.booleanReturns whether the metric is precomputedrender(ARXConfiguration config) Renders the privacy modeltoString()Returns the name of metric.Von Klasse geerbte Methoden org.deidentifier.arx.metric.v2.MetricMDNUNMEntropyPrecomputed
isGSFactorSupportedVon Klasse geerbte Methoden org.deidentifier.arx.metric.v2.MetricMDNUEntropyPrecomputed
getInformationLossInternalRaw, getScore, getUpperBounds, initialize, isScoreFunctionSupportedVon Klasse geerbte Methoden org.deidentifier.arx.metric.v2.AbstractMetricMultiDimensional
createInformationLoss, createMaxInformationLoss, createMinInformationLoss, getAggregateFunction, getAggregationFunctionsGeneralized, getAggregationFunctionsNonGeneralized, getAggregationIndicesGeneralized, getAggregationIndicesNonGeneralized, getAggregationInformation, getDimensions, getDimensionsAggregated, getDimensionsGeneralized, initialize, setMax, setMinVon 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, getDescription, getGeneralizationFactor, getGeneralizationSuppressionFactor, getInformationLoss, getInformationLoss, getLowerBound, getLowerBound, getNumRecords, getSubset, getSuppressionFactor, initialize, isAbleToHandleClusteredMicroaggregation, isAbleToHandleMicroaggregation, isIndependent, isMonotonic, isMonotonicWithGeneralization, isMonotonicWithSuppression, isMultiDimensional, isWeighted, list, round
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Konstruktordetails
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MetricMDNUNMNormalizedEntropyPrecomputed
Creates a new instance.- Parameter:
function-
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MetricMDNUNMNormalizedEntropyPrecomputed
protected MetricMDNUNMNormalizedEntropyPrecomputed()Creates a new instance.
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Methodendetails
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getConfiguration
Returns the configuration of this metric.- Setzt außer Kraft:
getConfigurationin KlasseMetricMDNUNMEntropyPrecomputed- Gibt zurück:
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getName
Beschreibung aus Klasse kopiert:MetricReturns the name of metric.- Setzt außer Kraft:
getNamein KlasseMetric<AbstractILMultiDimensional>- Gibt zurück:
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isPrecomputed
public boolean isPrecomputed()Beschreibung aus Klasse kopiert:MetricReturns whether the metric is precomputed- Setzt außer Kraft:
isPrecomputedin KlasseMetricMDNUNMEntropyPrecomputed- Gibt zurück:
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render
Beschreibung aus Klasse kopiert:MetricRenders the privacy model- Setzt außer Kraft:
renderin KlasseMetricMDNUNMEntropyPrecomputed- Gibt zurück:
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toString
Beschreibung aus Klasse kopiert:MetricReturns the name of metric.- Setzt außer Kraft:
toStringin KlasseMetricMDNUNMEntropyPrecomputed- Gibt zurück:
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getInformationLossInternal
protected ILMultiDimensionalWithBound getInformationLossInternal(org.deidentifier.arx.framework.lattice.Transformation<?> node, org.deidentifier.arx.framework.check.groupify.HashGroupify g) Beschreibung aus Klasse kopiert:MetricEvaluates the metric for the given node.- Setzt außer Kraft:
getInformationLossInternalin KlasseMetricMDNUNMEntropyPrecomputed- 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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getInformationLossInternal
protected ILMultiDimensionalWithBound getInformationLossInternal(org.deidentifier.arx.framework.lattice.Transformation<?> node, org.deidentifier.arx.framework.check.groupify.HashGroupifyEntry entry) Beschreibung aus Klasse kopiert:MetricReturns the information loss that would be induced by suppressing the given entry. The loss is not necessarily consistent with the loss that is computed bygetInformationLoss(node, groupify)but is guaranteed to be comparable for different entries from the same groupify operator.- Setzt außer Kraft:
getInformationLossInternalin KlasseMetricMDNUEntropyPrecomputed- Parameter:
entry-- Gibt zurück:
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getLowerBoundInternal
protected AbstractILMultiDimensional getLowerBoundInternal(org.deidentifier.arx.framework.lattice.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 KlasseMetricMDNUNMEntropyPrecomputed- Parameter:
node-- Gibt zurück:
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getLowerBoundInternal
protected AbstractILMultiDimensional getLowerBoundInternal(org.deidentifier.arx.framework.lattice.Transformation<?> node, org.deidentifier.arx.framework.check.groupify.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 KlasseMetricMDNUNMEntropyPrecomputed- Parameter:
node-groupify-- Gibt zurück:
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initializeInternal
protected void initializeInternal(org.deidentifier.arx.framework.data.DataManager manager, DataDefinition definition, org.deidentifier.arx.framework.data.Data input, org.deidentifier.arx.framework.data.GeneralizationHierarchy[] hierarchies, ARXConfiguration config) Beschreibung aus Klasse kopiert:MetricImplement this to initialize the metric.- Setzt außer Kraft:
initializeInternalin KlasseMetricMDNUNMEntropyPrecomputed- Parameter:
manager-definition-input-hierarchies-config-
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