public class MetricMDNMLoss extends AbstractMetricMultiDimensional
Metric.AggregateFunction
Constructor and Description |
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MetricMDNMLoss()
Default constructor which treats all transformation methods equally.
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MetricMDNMLoss(double gsFactor,
Metric.AggregateFunction function)
A constructor that allows to define a factor weighting generalization and suppression.
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MetricMDNMLoss(Metric.AggregateFunction function)
Default constructor which treats all transformation methods equally.
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Modifier and Type | Method and Description |
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MetricConfiguration |
getConfiguration()
Returns the configuration of this metric.
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double |
getGeneralizationFactor()
Returns the factor used weight generalized values.
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double |
getGeneralizationSuppressionFactor()
Returns the factor weighting generalization and suppression.
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java.lang.String |
getName()
Returns the name of metric.
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ILScore |
getScore(Transformation<?> node,
HashGroupify groupify)
Calculates the score.
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double |
getSuppressionFactor()
Returns the factor used to weight suppressed values.
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boolean |
isAbleToHandleMicroaggregation()
Returns whether this metric handles microaggregation
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boolean |
isGSFactorSupported()
Returns whether a generalization/suppression factor is supported
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boolean |
isScoreFunctionSupported()
Returns whether the metric provides a score function
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ElementData |
render(ARXConfiguration config)
Renders the privacy model
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java.lang.String |
toString()
Returns the name of metric.
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createMaxInformationLoss, createMinInformationLoss, getAggregateFunction
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, getInformationLoss, getInformationLoss, getLowerBound, getLowerBound, initialize, isAbleToHandleClusteredMicroaggregation, isIndependent, isMonotonic, isMonotonicWithGeneralization, isMonotonicWithSuppression, isMultiDimensional, isPrecomputed, isWeighted, list
public MetricMDNMLoss()
public MetricMDNMLoss(Metric.AggregateFunction function)
function
- public MetricMDNMLoss(double gsFactor, Metric.AggregateFunction function)
gsFactor
- A factor [0,1] weighting generalization and suppression.
The default value is 0.5, which means that generalization
and suppression will be treated equally. A factor of 0
will favor suppression, and a factor of 1 will favor
generalization. The values in between can be used for
balancing both methods.function
- public MetricConfiguration getConfiguration()
getConfiguration
in class Metric<AbstractILMultiDimensional>
public double getGeneralizationFactor()
Metric
getGeneralizationFactor
in class Metric<AbstractILMultiDimensional>
public double getGeneralizationSuppressionFactor()
Metric
getGeneralizationSuppressionFactor
in class Metric<AbstractILMultiDimensional>
public java.lang.String getName()
Metric
getName
in class Metric<AbstractILMultiDimensional>
public ILScore getScore(Transformation<?> node, HashGroupify groupify)
Metric
getScore
in class Metric<AbstractILMultiDimensional>
public double getSuppressionFactor()
Metric
getSuppressionFactor
in class Metric<AbstractILMultiDimensional>
public boolean isAbleToHandleMicroaggregation()
Metric
isAbleToHandleMicroaggregation
in class Metric<AbstractILMultiDimensional>
public boolean isGSFactorSupported()
Metric
isGSFactorSupported
in class Metric<AbstractILMultiDimensional>
public boolean isScoreFunctionSupported()
Metric
isScoreFunctionSupported
in class Metric<AbstractILMultiDimensional>
public ElementData render(ARXConfiguration config)
Metric
render
in class Metric<AbstractILMultiDimensional>
public java.lang.String toString()
Metric
toString
in class Metric<AbstractILMultiDimensional>