public class MetricMDNUEntropyPrecomputed extends AbstractMetricMultiDimensional
Metric.AggregateFunction
Constructor and Description |
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MetricMDNUEntropyPrecomputed(boolean monotonicWithGeneralization,
boolean monotonicWithSuppression,
boolean independent,
double gsFactor,
Metric.AggregateFunction function)
Precomputed.
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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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ILScore |
getScore(Transformation<?> node,
HashGroupify groupify)
Calculates the score.
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boolean |
isGSFactorSupported()
Returns whether a generalization/suppression factor is supported
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boolean |
isPrecomputed()
Returns whether the metric is precomputed
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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, getGeneralizationFactor, getGeneralizationSuppressionFactor, getInformationLoss, getInformationLoss, getLowerBound, getLowerBound, getName, getSuppressionFactor, initialize, isAbleToHandleClusteredMicroaggregation, isAbleToHandleMicroaggregation, isIndependent, isMonotonic, isMonotonicWithGeneralization, isMonotonicWithSuppression, isMultiDimensional, isWeighted, list
public MetricMDNUEntropyPrecomputed(boolean monotonicWithGeneralization, boolean monotonicWithSuppression, boolean independent, double gsFactor, Metric.AggregateFunction function)
monotonicWithGeneralization
- monotonicWithSuppression
- independent
- gsFactor
- function
- public MetricConfiguration getConfiguration()
getConfiguration
in class Metric<AbstractILMultiDimensional>
public ILScore getScore(Transformation<?> node, HashGroupify groupify)
Metric
getScore
in class Metric<AbstractILMultiDimensional>
public boolean isGSFactorSupported()
Metric
isGSFactorSupported
in class Metric<AbstractILMultiDimensional>
public boolean isPrecomputed()
Metric
isPrecomputed
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>