Package org.deidentifier.arx.metric
Klasse MetricNMPrecision
java.lang.Object
org.deidentifier.arx.metric.Metric<org.deidentifier.arx.metric.InformationLossDefault>
org.deidentifier.arx.metric.MetricWeighted<org.deidentifier.arx.metric.InformationLossDefault>
org.deidentifier.arx.metric.MetricNMPrecision
- Alle implementierten Schnittstellen:
Serializable
public class MetricNMPrecision
extends MetricWeighted<org.deidentifier.arx.metric.InformationLossDefault>
This class provides an implementation of a weighted precision metric as
proposed in:
Sweeney, L. (2002). Achieving k-anonymity privacy protection using generalization and suppression.
International Journal of Uncertainty Fuzziness and, 10(5), 2002.
This metric will respect attribute weights defined in the configuration.
Sweeney, L. (2002). Achieving k-anonymity privacy protection using generalization and suppression.
International Journal of Uncertainty Fuzziness and, 10(5), 2002.
This metric will respect attribute weights defined in the configuration.
- 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.MetricWeighted
weights -
Konstruktorübersicht
Konstruktoren -
Methodenübersicht
Modifizierer und TypMethodeBeschreibungReturns an instance of the maximal value.Returns an instance of the minimal value.protected doublegetCells()Returns the number of cells.protected int[]protected InformationLossWithBound<org.deidentifier.arx.metric.InformationLossDefault> getInformationLossInternal(org.deidentifier.arx.framework.lattice.Transformation<?> node, org.deidentifier.arx.framework.check.groupify.HashGroupify g) Evaluates the metric for the given node.protected InformationLossWithBound<org.deidentifier.arx.metric.InformationLossDefault> getInformationLossInternal(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 org.deidentifier.arx.metric.InformationLossDefaultgetLowerBoundInternal(org.deidentifier.arx.framework.lattice.Transformation<?> node) Returns a lower bound for the information loss for the given node.protected org.deidentifier.arx.metric.InformationLossDefaultgetLowerBoundInternal(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.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.render(ARXConfiguration config) Renders the privacy modeltoString()Returns the name of metric.Von 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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MetricNMPrecision
protected MetricNMPrecision()Creates a new instance.
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Methodendetails
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createMaxInformationLoss
Beschreibung aus Klasse kopiert:MetricReturns an instance of the maximal value.- Angegeben von:
createMaxInformationLossin KlasseMetric<org.deidentifier.arx.metric.InformationLossDefault>- Gibt zurück:
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createMinInformationLoss
Beschreibung aus Klasse kopiert:MetricReturns an instance of the minimal value.- Angegeben von:
createMinInformationLossin KlasseMetric<org.deidentifier.arx.metric.InformationLossDefault>- Gibt zurück:
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render
Beschreibung aus Klasse kopiert:MetricRenders the privacy model -
toString
Beschreibung aus Klasse kopiert:MetricReturns the name of metric. -
getCells
protected double getCells()Returns the number of cells.- Gibt zurück:
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getHeights
protected int[] getHeights()- Gibt zurück:
- the heights
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getInformationLossInternal
protected InformationLossWithBound<org.deidentifier.arx.metric.InformationLossDefault> 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.- Angegeben von:
getInformationLossInternalin KlasseMetric<org.deidentifier.arx.metric.InformationLossDefault>- 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 InformationLossWithBound<org.deidentifier.arx.metric.InformationLossDefault> 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.- Angegeben von:
getInformationLossInternalin KlasseMetric<org.deidentifier.arx.metric.InformationLossDefault>- Parameter:
entry-- Gibt zurück:
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getLowerBoundInternal
protected org.deidentifier.arx.metric.InformationLossDefault 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 KlasseMetricWeighted<org.deidentifier.arx.metric.InformationLossDefault>- Parameter:
node-- Gibt zurück:
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getLowerBoundInternal
protected org.deidentifier.arx.metric.InformationLossDefault 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 KlasseMetricWeighted<org.deidentifier.arx.metric.InformationLossDefault>- 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 KlasseMetricWeighted<org.deidentifier.arx.metric.InformationLossDefault>- Parameter:
manager-definition-input-hierarchies-config-
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