public abstract class AbstractMetricSingleDimensional extends Metric<ILSingleDimensional>
Metric.AggregateFunction
Modifier | Constructor and Description |
---|---|
protected |
AbstractMetricSingleDimensional(boolean monotonicWithGeneralization,
boolean monotonicWithSuppression,
boolean independent)
Creates a new instance.
|
protected |
AbstractMetricSingleDimensional(boolean monotonicWithGeneralization,
boolean monotonicWithSuppression,
boolean independent,
double gsFactor)
Creates a new instance.
|
Modifier and Type | Method and Description |
---|---|
ILSingleDimensional |
createInformationLoss(double loss)
Create a loss object
|
ILSingleDimensionalWithBound |
createInformationLoss(double loss,
double bound)
Create a loss object
|
InformationLoss<?> |
createMaxInformationLoss()
Returns an instance of the maximal value.
|
InformationLoss<?> |
createMinInformationLoss()
Returns an instance of the minimal value.
|
protected int |
getDimensions()
Returns the number of dimensions.
|
protected int |
getDimensionsAggregated()
Returns the number of dimensions.
|
protected int |
getDimensionsGeneralized()
Returns the number of dimensions.
|
protected int[] |
getMicroaggregationDomainSizes()
Needed for microaggregation
|
protected DistributionAggregateFunction[] |
getMicroaggregationFunctions()
Needed for microaggregation
|
protected int |
getMicroaggregationStartIndex()
Needed for microaggregation
|
protected java.lang.Double |
getNumTuples()
Returns the number of rows in the dataset or subset.
|
protected void |
initializeInternal(DataManager manager,
DataDefinition definition,
Data input,
GeneralizationHierarchy[] hierarchies,
ARXConfiguration config)
Implement this to initialize the metric.
|
protected void |
setNumTuples(java.lang.Double tuples)
Returns the number of rows in the dataset or subset.
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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, getAggregateFunction, getConfiguration, getDescription, getDescription, getGeneralizationFactor, getGeneralizationSuppressionFactor, getInformationLoss, getInformationLoss, getInformationLossInternal, getInformationLossInternal, getLowerBound, getLowerBound, getLowerBoundInternal, getLowerBoundInternal, getName, getNumRecords, getSubset, getSuppressionFactor, initialize, isAbleToHandleMicroaggregation, isGSFactorSupported, isIndependent, isMonotonic, isMonotonicWithGeneralization, isMonotonicWithSuppression, isMultiDimensional, isPrecomputed, isWeighted, list, round, toString
protected AbstractMetricSingleDimensional(boolean monotonicWithGeneralization, boolean monotonicWithSuppression, boolean independent)
monotonicWithGeneralization
- monotonicWithSuppression
- independent
- protected AbstractMetricSingleDimensional(boolean monotonicWithGeneralization, boolean monotonicWithSuppression, boolean independent, double gsFactor)
monotonicWithGeneralization
- monotonicWithSuppression
- independent
- gsFactor
- public ILSingleDimensional createInformationLoss(double loss)
loss
- public ILSingleDimensionalWithBound createInformationLoss(double loss, double bound)
loss
- bound
- public InformationLoss<?> createMaxInformationLoss()
Metric
createMaxInformationLoss
in class Metric<ILSingleDimensional>
public InformationLoss<?> createMinInformationLoss()
Metric
createMinInformationLoss
in class Metric<ILSingleDimensional>
protected int getDimensions()
protected int getDimensionsAggregated()
protected int getDimensionsGeneralized()
protected int[] getMicroaggregationDomainSizes()
protected DistributionAggregateFunction[] getMicroaggregationFunctions()
protected int getMicroaggregationStartIndex()
protected java.lang.Double getNumTuples()
protected void initializeInternal(DataManager manager, DataDefinition definition, Data input, GeneralizationHierarchy[] hierarchies, ARXConfiguration config)
Metric
initializeInternal
in class Metric<ILSingleDimensional>
protected void setNumTuples(java.lang.Double tuples)
tuples
-