public class MetricMDNUEntropyPrecomputed extends AbstractMetricMultiDimensional
Metric.AggregateFunction
Modifier | Constructor and Description |
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protected |
MetricMDNUEntropyPrecomputed()
Creates a new instance.
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MetricMDNUEntropyPrecomputed(boolean monotonicWithGeneralization,
boolean monotonicWithSuppression,
boolean independent,
double gsFactor,
Metric.AggregateFunction function)
Precomputed.
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protected |
MetricMDNUEntropyPrecomputed(double gsFactor,
Metric.AggregateFunction function)
Creates a new instance.
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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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protected ILMultiDimensionalWithBound |
getInformationLossInternal(org.deidentifier.arx.framework.lattice.Transformation node,
org.deidentifier.arx.framework.check.groupify.HashGroupify g)
Evaluates the metric for the given node.
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protected ILMultiDimensionalWithBound |
getInformationLossInternal(org.deidentifier.arx.framework.lattice.Transformation node,
org.deidentifier.arx.framework.check.groupify.HashGroupifyEntry entry)
Returns the information loss that would be induced by suppressing the given entry.
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protected double[] |
getInformationLossInternalRaw(org.deidentifier.arx.framework.lattice.Transformation node,
org.deidentifier.arx.framework.check.groupify.HashGroupify g) |
protected AbstractILMultiDimensional |
getLowerBoundInternal(org.deidentifier.arx.framework.lattice.Transformation node)
Returns a lower bound for the information loss for the given node.
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protected AbstractILMultiDimensional |
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.
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protected double[] |
getUpperBounds()
Returns the upper bound of the entropy value per column
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protected void |
initialize(double[][] cache,
int[][][] cardinalities,
int[][][] hierarchies)
For backwards compatibility.
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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.
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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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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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createInformationLoss, createInformationLossWithBound, createInformationLossWithoutBound, createMaxInformationLoss, createMinInformationLoss, getAggregateFunction, getAggregateFunctions, getDimensions, getDimensionsAggregated, getDimensionsGeneralized, getError, getMicroaggregationFunctions, getMicroaggregationStartIndex, initialize, setMax, setMin
createAECSMetric, createAECSMetric, createAmbiguityMetric, 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, getGeneralizationFactor, getGeneralizationSuppressionFactor, getInformationLoss, getInformationLoss, getLowerBound, getLowerBound, getName, getNumRecords, getSubset, getSuppressionFactor, initialize, isAbleToHandleMicroaggregation, isIndependent, isMonotonic, isMonotonicWithGeneralization, isMonotonicWithSuppression, isMultiDimensional, isWeighted, list, round
public MetricMDNUEntropyPrecomputed(boolean monotonicWithGeneralization, boolean monotonicWithSuppression, boolean independent, double gsFactor, Metric.AggregateFunction function)
monotonicWithGeneralization
- monotonicWithSuppression
- independent
- gsFactor
- function
- protected MetricMDNUEntropyPrecomputed()
protected MetricMDNUEntropyPrecomputed(double gsFactor, Metric.AggregateFunction function)
gsFactor
- function
- public MetricConfiguration getConfiguration()
getConfiguration
in class Metric<AbstractILMultiDimensional>
public boolean isGSFactorSupported()
Metric
isGSFactorSupported
in class Metric<AbstractILMultiDimensional>
public boolean isPrecomputed()
Metric
isPrecomputed
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>
protected ILMultiDimensionalWithBound getInformationLossInternal(org.deidentifier.arx.framework.lattice.Transformation node, org.deidentifier.arx.framework.check.groupify.HashGroupify g)
Metric
getInformationLossInternal
in class Metric<AbstractILMultiDimensional>
node
- The node for which to compute the information lossg
- The groupify operator of the previous checkprotected ILMultiDimensionalWithBound getInformationLossInternal(org.deidentifier.arx.framework.lattice.Transformation node, org.deidentifier.arx.framework.check.groupify.HashGroupifyEntry entry)
Metric
getInformationLoss(node, groupify)
but is guaranteed to be comparable for
different entries from the same groupify operator.getInformationLossInternal
in class Metric<AbstractILMultiDimensional>
protected double[] getInformationLossInternalRaw(org.deidentifier.arx.framework.lattice.Transformation node, org.deidentifier.arx.framework.check.groupify.HashGroupify g)
node
- g
- protected AbstractILMultiDimensional getLowerBoundInternal(org.deidentifier.arx.framework.lattice.Transformation node)
Metric
null
.getLowerBoundInternal
in class Metric<AbstractILMultiDimensional>
protected AbstractILMultiDimensional getLowerBoundInternal(org.deidentifier.arx.framework.lattice.Transformation node, org.deidentifier.arx.framework.check.groupify.HashGroupify groupify)
Metric
null
. getLowerBoundInternal
in class Metric<AbstractILMultiDimensional>
protected double[] getUpperBounds()
protected void initialize(double[][] cache, int[][][] cardinalities, int[][][] hierarchies)
cache
- cardinalities
- hierarchies
- 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)
Metric
initializeInternal
in class AbstractMetricMultiDimensional