org.deidentifier.arx.metric.v2

Class MetricMDNUNMEntropy

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.MetricMDNUNMEntropy

All Implemented Interfaces:

java.io.Serializable

public class MetricMDNUNMEntropy
extends MetricMDNUNMEntropyPrecomputed

This class provides an implementation of the non-uniform entropy metric. See:
A. De Waal and L. Willenborg: "Information loss through global recoding and local suppression" Netherlands Off Stat, vol. 14, pp. 17–20, 1999.

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class org.deidentifier.arx.metric.Metric

Metric.AggregateFunction

Field Summary

Fields inherited from class org.deidentifier.arx.metric.v2.AbstractMetricMultiDimensional

k

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	MetricMDNUNMEntropy() Creates a new instance.
protected	MetricMDNUNMEntropy(double gsFactor, Metric.AggregateFunction function) Creates a new instance.

Method Summary

Modifier and Type	Method and Description
MetricConfiguration	getConfiguration() Returns the configuration of this metric.
protected AbstractILMultiDimensional	getLowerBoundInternal(org.deidentifier.arx.framework.lattice.Transformation<?> node) Returns a lower bound for the information loss for the given node.
boolean	isGSFactorSupported() Returns whether a generalization/suppression factor is supported
ElementData	render(ARXConfiguration config) Renders the privacy model
java.lang.String	toString() Returns the name of metric.

Methods inherited from class org.deidentifier.arx.metric.v2.MetricMDNUNMEntropyPrecomputed

getInformationLossInternal, getLowerBoundInternal, initializeInternal, isPrecomputed

Methods inherited from class org.deidentifier.arx.metric.v2.MetricMDNUEntropyPrecomputed

getInformationLossInternal, getInformationLossInternalRaw, getScore, getUpperBounds, initialize, isScoreFunctionSupported

Methods inherited from class org.deidentifier.arx.metric.v2.AbstractMetricMultiDimensional

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

Methods inherited from class 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, getName, getNumRecords, getSubset, getSuppressionFactor, initialize, isAbleToHandleClusteredMicroaggregation, isAbleToHandleMicroaggregation, isIndependent, isMonotonic, isMonotonicWithGeneralization, isMonotonicWithSuppression, isMultiDimensional, isWeighted, list, round

Methods inherited from class java.lang.Object

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

Constructor Detail

MetricMDNUNMEntropy

protected MetricMDNUNMEntropy()

Creates a new instance.

MetricMDNUNMEntropy

protected MetricMDNUNMEntropy(double gsFactor,
                              Metric.AggregateFunction function)

Creates a new instance.

Parameters:

gsFactor -

function -

Method Detail

getConfiguration

public MetricConfiguration getConfiguration()

Returns the configuration of this metric.

Overrides:

getConfiguration in class MetricMDNUNMEntropyPrecomputed

Returns:

isGSFactorSupported

public boolean isGSFactorSupported()

Description copied from class: Metric

Returns whether a generalization/suppression factor is supported

Overrides:

isGSFactorSupported in class MetricMDNUNMEntropyPrecomputed

Returns:

render

public ElementData render(ARXConfiguration config)

Description copied from class: Metric

Renders the privacy model

Overrides:

render in class MetricMDNUNMEntropyPrecomputed

Returns:

toString

public java.lang.String toString()

Description copied from class: Metric

Returns the name of metric.

Overrides:

toString in class MetricMDNUNMEntropyPrecomputed

getLowerBoundInternal

protected AbstractILMultiDimensional getLowerBoundInternal(org.deidentifier.arx.framework.lattice.Transformation<?> node)

Description copied from class: 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.

Overrides:

getLowerBoundInternal in class MetricMDNUNMEntropyPrecomputed

Returns: