org.deidentifier.arx.metric.v2

Class 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

All Implemented Interfaces:

java.io.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.

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	MetricMDNUNMNormalizedEntropyPotentiallyPrecomputed(double threshold) Creates a new instance.
protected	MetricMDNUNMNormalizedEntropyPotentiallyPrecomputed(double threshold, Metric.AggregateFunction function) Creates a new instance.

Method Summary

Modifier and Type	Method and Description
MetricConfiguration	getConfiguration() Returns the configuration of this metric.
java.lang.String	getName() Returns the name of metric.
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.AbstractMetricMultiDimensionalPotentiallyPrecomputed

createMaxInformationLoss, createMinInformationLoss, getAggregateFunction, getDefaultMetric, getGeneralizationFactor, getGeneralizationSuppressionFactor, getInformationLossInternal, getInformationLossInternal, getLowerBoundInternal, getLowerBoundInternal, getPrecomputedMetric, getScore, getSuppressionFactor, getThreshold, initializeInternal, isIndependent, isPrecomputed, isScoreFunctionSupported

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

createInformationLoss, 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, getInformationLoss, getInformationLoss, getLowerBound, getLowerBound, getNumRecords, getSubset, initialize, isAbleToHandleClusteredMicroaggregation, isAbleToHandleMicroaggregation, isGSFactorSupported, 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

MetricMDNUNMNormalizedEntropyPotentiallyPrecomputed

protected MetricMDNUNMNormalizedEntropyPotentiallyPrecomputed(double threshold)

Creates a new instance. The precomputed variant will be used if #distinctValues / #rows <= threshold for all quasi-identifiers.

Parameters:

threshold -

MetricMDNUNMNormalizedEntropyPotentiallyPrecomputed

protected MetricMDNUNMNormalizedEntropyPotentiallyPrecomputed(double threshold,
                                                              Metric.AggregateFunction function)

Creates a new instance. The pre-computed variant will be used if #distinctValues / #rows <= threshold for all quasi-identifiers.

Parameters:

threshold -

function -

Method Detail

getConfiguration

public MetricConfiguration getConfiguration()

Returns the configuration of this metric.

Overrides:

getConfiguration in class Metric<AbstractILMultiDimensional>

Returns:

getName

public java.lang.String getName()

Description copied from class: Metric

Returns the name of metric.

Overrides:

getName in class Metric<AbstractILMultiDimensional>

Returns:

render

public ElementData render(ARXConfiguration config)

Description copied from class: Metric

Renders the privacy model

Specified by:

render in class Metric<AbstractILMultiDimensional>

Returns:

toString

public java.lang.String toString()

Description copied from class: Metric

Returns the name of metric.

Overrides:

toString in class Metric<AbstractILMultiDimensional>