Package org.deidentifier.arx.metric.v2
Klasse MetricMDNUNMNormalizedEntropyPotentiallyPrecomputed
java.lang.Object
org.deidentifier.arx.metric.Metric<AbstractILMultiDimensional>
org.deidentifier.arx.metric.v2.AbstractMetricMultiDimensional
org.deidentifier.arx.metric.v2.AbstractMetricMultiDimensionalPotentiallyPrecomputed
org.deidentifier.arx.metric.v2.MetricMDNUNMNormalizedEntropyPotentiallyPrecomputed
- Alle implementierten Schnittstellen:
Serializable
public class MetricMDNUNMNormalizedEntropyPotentiallyPrecomputed
extends AbstractMetricMultiDimensionalPotentiallyPrecomputed
This class provides an 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:
-
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
k -
Konstruktorübersicht
KonstruktorenModifiziererKonstruktorBeschreibungprotectedMetricMDNUNMNormalizedEntropyPotentiallyPrecomputed(double threshold) Creates a new instance.protectedMetricMDNUNMNormalizedEntropyPotentiallyPrecomputed(double threshold, Metric.AggregateFunction function) Creates a new instance. -
Methodenübersicht
Modifizierer und TypMethodeBeschreibungReturns the configuration of this metric.getName()Returns the name of metric.render(ARXConfiguration config) Renders the privacy modeltoString()Returns the name of metric.Von Klasse geerbte Methoden org.deidentifier.arx.metric.v2.AbstractMetricMultiDimensionalPotentiallyPrecomputed
createMaxInformationLoss, createMinInformationLoss, getAggregateFunction, getDefaultMetric, getGeneralizationFactor, getGeneralizationSuppressionFactor, getInformationLossInternal, getInformationLossInternal, getLowerBoundInternal, getLowerBoundInternal, getPrecomputedMetric, getScore, getSuppressionFactor, getThreshold, initializeInternal, isIndependent, isPrecomputed, isScoreFunctionSupportedVon Klasse geerbte Methoden org.deidentifier.arx.metric.v2.AbstractMetricMultiDimensional
createInformationLoss, 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, getInformationLoss, getInformationLoss, getLowerBound, getLowerBound, getNumRecords, getSubset, initialize, isAbleToHandleClusteredMicroaggregation, isAbleToHandleMicroaggregation, isGSFactorSupported, isMonotonic, isMonotonicWithGeneralization, isMonotonicWithSuppression, isMultiDimensional, isWeighted, list, round
-
Konstruktordetails
-
MetricMDNUNMNormalizedEntropyPotentiallyPrecomputed
protected MetricMDNUNMNormalizedEntropyPotentiallyPrecomputed(double threshold) Creates a new instance. The precomputed variant will be used if #distinctValues / #rows Ungültige Eingabe: "<"= threshold for all quasi-identifiers.- Parameter:
threshold-
-
MetricMDNUNMNormalizedEntropyPotentiallyPrecomputed
protected MetricMDNUNMNormalizedEntropyPotentiallyPrecomputed(double threshold, Metric.AggregateFunction function) Creates a new instance. The pre-computed variant will be used if #distinctValues / #rows Ungültige Eingabe: "<"= threshold for all quasi-identifiers.- Parameter:
threshold-function-
-
-
Methodendetails
-
getConfiguration
Returns the configuration of this metric.- Setzt außer Kraft:
getConfigurationin KlasseMetric<AbstractILMultiDimensional>- Gibt zurück:
-
getName
Beschreibung aus Klasse kopiert:MetricReturns the name of metric.- Setzt außer Kraft:
getNamein KlasseMetric<AbstractILMultiDimensional>- Gibt zurück:
-
render
Beschreibung aus Klasse kopiert:MetricRenders the privacy model- Angegeben von:
renderin KlasseMetric<AbstractILMultiDimensional>- Gibt zurück:
-
toString
Beschreibung aus Klasse kopiert:MetricReturns the name of metric.- Setzt außer Kraft:
toStringin KlasseMetric<AbstractILMultiDimensional>- Gibt zurück:
-