org.deidentifier.arx.metric.v2

Class MetricMDNMLossPrecomputed

java.lang.Object

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

org.deidentifier.arx.metric.v2.AbstractMetricMultiDimensional

org.deidentifier.arx.metric.v2.MetricMDNMLoss

org.deidentifier.arx.metric.v2.MetricMDNMLossPrecomputed

All Implemented Interfaces:

java.io.Serializable

public class MetricMDNMLossPrecomputed
extends MetricMDNMLoss

This class implements a variant of the Loss metric. TODO: Add reference.

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	MetricMDNMLossPrecomputed() Creates a new instance.
protected	MetricMDNMLossPrecomputed(double gsFactor, Metric.AggregateFunction function) Creates a new instance.
protected	MetricMDNMLossPrecomputed(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.
protected AbstractILMultiDimensional	getLowerBoundInternal(org.deidentifier.arx.framework.lattice.Transformation<?> node, org.deidentifier.arx.framework.check.groupify.HashGroupify g) 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.
boolean	isAbleToHandleMicroaggregation() Returns whether this metric handles microaggregation
boolean	isGSFactorSupported() Returns whether a generalization/suppression factor is supported
boolean	isPrecomputed() Returns whether the metric is precomputed
ElementData	render(ARXConfiguration config) Renders the privacy model

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

getGeneralizationFactor, getGeneralizationSuppressionFactor, getInformationLossInternal, getInformationLossInternal, getName, getScore, getShares, getSuppressionFactor, isScoreFunctionSupported, normalizeAggregated, normalizeGeneralized, toString

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, getInformationLoss, getInformationLoss, getLowerBound, getLowerBound, getNumRecords, getSubset, initialize, isAbleToHandleClusteredMicroaggregation, 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

MetricMDNMLossPrecomputed

protected MetricMDNMLossPrecomputed()

Creates a new instance.

MetricMDNMLossPrecomputed

protected MetricMDNMLossPrecomputed(Metric.AggregateFunction function)

Creates a new instance.

Parameters:

function -

MetricMDNMLossPrecomputed

protected MetricMDNMLossPrecomputed(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 MetricMDNMLoss

Returns:

isAbleToHandleMicroaggregation

public boolean isAbleToHandleMicroaggregation()

Description copied from class: Metric

Returns whether this metric handles microaggregation

Overrides:

isAbleToHandleMicroaggregation in class MetricMDNMLoss

Returns:

isGSFactorSupported

public boolean isGSFactorSupported()

Description copied from class: Metric

Returns whether a generalization/suppression factor is supported

Overrides:

isGSFactorSupported in class MetricMDNMLoss

Returns:

isPrecomputed

public boolean isPrecomputed()

Description copied from class: Metric

Returns whether the metric is precomputed

Overrides:

isPrecomputed in class Metric<AbstractILMultiDimensional>

Returns:

render

public ElementData render(ARXConfiguration config)

Description copied from class: Metric

Renders the privacy model

Overrides:

render in class MetricMDNMLoss

Returns:

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 MetricMDNMLoss

Returns:

getLowerBoundInternal

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

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!

Overrides:

getLowerBoundInternal in class MetricMDNMLoss

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.

Overrides:

initializeInternal in class MetricMDNMLoss