org.deidentifier.arx.metric

Class MetricDefault

java.lang.Object

org.deidentifier.arx.metric.Metric<org.deidentifier.arx.metric.InformationLossDefault>

org.deidentifier.arx.metric.MetricDefault

All Implemented Interfaces:

java.io.Serializable

Direct Known Subclasses:

MetricAECS, MetricDM, MetricDMStar, MetricEntropy, MetricHeight

public abstract class MetricDefault
extends Metric<org.deidentifier.arx.metric.InformationLossDefault>

This class provides an abstract skeleton for the implementation of metrics.

See Also:

Serialized Form

Nested Class Summary

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

Metric.AggregateFunction

Constructor Summary

Constructors

Constructor and Description
MetricDefault(boolean monotonicWithGeneralization, boolean monotonicWithSuppression, boolean independent)

Method Summary

Modifier and Type	Method and Description
InformationLoss<?>	createMaxInformationLoss() Returns an instance of the maximal value.
InformationLoss<?>	createMinInformationLoss() Returns an instance of the minimal value.
protected org.deidentifier.arx.metric.InformationLossDefault	getLowerBoundInternal(org.deidentifier.arx.framework.lattice.Transformation<?> node) Returns a lower bound for the information loss for the given node.
protected org.deidentifier.arx.metric.InformationLossDefault	getLowerBoundInternal(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 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) Implement this to initialize the metric.

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, getAggregateFunction, getConfiguration, getDescription, getDescription, getGeneralizationFactor, getGeneralizationSuppressionFactor, getInformationLoss, getInformationLoss, getInformationLossInternal, getInformationLossInternal, getLowerBound, getLowerBound, getName, getNumRecords, getScore, getSubset, getSuppressionFactor, initialize, isAbleToHandleClusteredMicroaggregation, isAbleToHandleMicroaggregation, isGSFactorSupported, isIndependent, isMonotonic, isMonotonicWithGeneralization, isMonotonicWithSuppression, isMultiDimensional, isPrecomputed, isScoreFunctionSupported, isWeighted, list, render, round, toString

Methods inherited from class java.lang.Object

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

Constructor Detail

MetricDefault

public MetricDefault(boolean monotonicWithGeneralization,
                     boolean monotonicWithSuppression,
                     boolean independent)

Parameters:

monotonicWithGeneralization -

monotonicWithSuppression -

independent -

Method Detail

createMaxInformationLoss

public InformationLoss<?> createMaxInformationLoss()

Description copied from class: Metric

Returns an instance of the maximal value.

Specified by:

createMaxInformationLoss in class Metric<org.deidentifier.arx.metric.InformationLossDefault>

Returns:

createMinInformationLoss

public InformationLoss<?> createMinInformationLoss()

Description copied from class: Metric

Returns an instance of the minimal value.

Specified by:

createMinInformationLoss in class Metric<org.deidentifier.arx.metric.InformationLossDefault>

Returns:

getLowerBoundInternal

protected org.deidentifier.arx.metric.InformationLossDefault 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.

Specified by:

getLowerBoundInternal in class Metric<org.deidentifier.arx.metric.InformationLossDefault>

Returns:

getLowerBoundInternal

protected org.deidentifier.arx.metric.InformationLossDefault getLowerBoundInternal(org.deidentifier.arx.framework.lattice.Transformation<?> node,
                                                                                   org.deidentifier.arx.framework.check.groupify.HashGroupify groupify)

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.

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!

Specified by:

getLowerBoundInternal in class Metric<org.deidentifier.arx.metric.InformationLossDefault>

Returns:

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)

Description copied from class: Metric

Implement this to initialize the metric.

Specified by:

initializeInternal in class Metric<org.deidentifier.arx.metric.InformationLossDefault>