Package org.deidentifier.arx.metric.v2

Klasse MetricMDNUNMNormalizedEntropy

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

org.deidentifier.arx.metric.v2.MetricMDNUNMNormalizedEntropy

Alle implementierten Schnittstellen:

Serializable

public class MetricMDNUNMNormalizedEntropy
extends MetricMDNUNMNormalizedEntropyPrecomputed

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.

Siehe auch:

• Serialisierte Form

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

Konstruktoren

Modifizierer	Konstruktor	Beschreibung
protected	MetricMDNUNMNormalizedEntropy()	Creates a new instance.
protected	MetricMDNUNMNormalizedEntropy(Metric.AggregateFunction function)	Creates a new instance.

Methodenübersicht

Modifizierer und Typ	Methode	Beschreibung
MetricConfiguration	getConfiguration()	Returns the configuration of this metric.
protected AbstractILMultiDimensional	getLowerBoundInternal(Transformation<?> node)	Returns a lower bound for the information loss for the given node.
String	getName()	Returns the name of metric.
ElementData	render(ARXConfiguration config)	Renders the privacy model
String	toString()	Returns the name of metric.

Von Klasse geerbte Methoden org.deidentifier.arx.metric.v2.MetricMDNUNMNormalizedEntropyPrecomputed

getInformationLossInternal, getInformationLossInternal, getLowerBoundInternal, initializeInternal, isPrecomputed

Von Klasse geerbte Methoden org.deidentifier.arx.metric.v2.MetricMDNUNMEntropyPrecomputed

isGSFactorSupported

Von Klasse geerbte Methoden org.deidentifier.arx.metric.v2.MetricMDNUEntropyPrecomputed

getInformationLossInternalRaw, getScore, getUpperBounds, initialize, isScoreFunctionSupported

Von Klasse geerbte Methoden org.deidentifier.arx.metric.v2.AbstractMetricMultiDimensional

createInformationLoss, createMaxInformationLoss, createMinInformationLoss, getAggregateFunction, getAggregationFunctionsGeneralized, getAggregationFunctionsNonGeneralized, getAggregationIndicesGeneralized, getAggregationIndicesNonGeneralized, getAggregationInformation, getDimensions, getDimensionsAggregated, getDimensionsGeneralized, initialize, setMax, setMin

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, getDescription, getDescription, getGeneralizationFactor, getGeneralizationSuppressionFactor, getInformationLoss, getInformationLoss, getLowerBound, getLowerBound, getNumRecords, getSubset, getSuppressionFactor, initialize, isAbleToHandleClusteredMicroaggregation, isAbleToHandleMicroaggregation, isIndependent, isMonotonic, isMonotonicWithGeneralization, isMonotonicWithSuppression, isMultiDimensional, isWeighted, list, round

Von Klasse geerbte Methoden java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Konstruktordetails

MetricMDNUNMNormalizedEntropy

protected MetricMDNUNMNormalizedEntropy()

Creates a new instance.

MetricMDNUNMNormalizedEntropy

protected MetricMDNUNMNormalizedEntropy(Metric.AggregateFunction function)

Creates a new instance.

Parameter:

function -

Methodendetails

getConfiguration

public MetricConfiguration getConfiguration()

Returns the configuration of this metric.

Setzt außer Kraft:

getConfiguration in Klasse MetricMDNUNMNormalizedEntropyPrecomputed

Gibt zurück:

getName

public String getName()

Beschreibung aus Klasse kopiert: Metric

Returns the name of metric.

Setzt außer Kraft:

getName in Klasse MetricMDNUNMNormalizedEntropyPrecomputed

Gibt zurück:

render

public ElementData render(ARXConfiguration config)

Beschreibung aus Klasse kopiert: Metric

Renders the privacy model

Setzt außer Kraft:

render in Klasse MetricMDNUNMNormalizedEntropyPrecomputed

Gibt zurück:

toString

public String toString()

Beschreibung aus Klasse kopiert: Metric

Returns the name of metric.

Setzt außer Kraft:

toString in Klasse MetricMDNUNMNormalizedEntropyPrecomputed

Gibt zurück:

getLowerBoundInternal

protected AbstractILMultiDimensional getLowerBoundInternal(Transformation<?> node)

Beschreibung aus Klasse kopiert: Metric

Returns 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 return null.

Setzt außer Kraft:

getLowerBoundInternal in Klasse MetricMDNUNMNormalizedEntropyPrecomputed

Parameter:

node -

Gibt zurück: