## Uses of Class
org.deidentifier.arx.metric.InformationLoss

Packages that use InformationLoss
org.deidentifier.arx: This package provides the public API for the ARX anonymization framework.
org.deidentifier.arx.framework.check: This package implements the core functionality of the ARX framework, i.e., a highly efficient check for k-anonymity
org.deidentifier.arx.framework.lattice: This package provides the internal generalization lattice
org.deidentifier.arx.metric: Package providing access to quality models
org.deidentifier.arx.metric.v2: Main package implementing quality models

### Uses of InformationLoss in org.deidentifier.arx

Methods in org.deidentifier.arx that return InformationLoss
`InformationLoss<?>` ARXLattice.`getHighestScore()` Returns the highest score.
`InformationLoss<?>` ARXLattice.ARXNode.`getHighestScore()` Returns the highest score.
`InformationLoss<?>` ARXLattice.`getLowestScore()` Returns the lowest score.
`InformationLoss<?>` ARXLattice.ARXNode.`getLowestScore()` Returns the highest score.
`InformationLoss<?>` ARXProcessStatistics.Step.`getScore()` Returns a node's lower bound, if any.

Methods in org.deidentifier.arx with parameters of type InformationLoss
`void` ARXLattice.ARXNode.Access.`setHighestScore(InformationLoss<?> a)` Sets the maximal information loss.
`void` ARXLattice.ARXNode.Access.`setLowerBound(InformationLoss<?> a)` Sets the lower bound.
`void` ARXLattice.ARXNode.Access.`setLowestScore(InformationLoss<?> a)` Sets the minimal information loss.

### Uses of InformationLoss in org.deidentifier.arx.framework.check

Fields in org.deidentifier.arx.framework.check declared as InformationLoss
`InformationLoss<?>` TransformationResult.`informationLoss` Information loss.
`InformationLoss<?>` TransformationResult.`lowerBound` Lower bound.

### Uses of InformationLoss in org.deidentifier.arx.framework.lattice

Methods in org.deidentifier.arx.framework.lattice that return InformationLoss
`InformationLoss<?>` Transformation.`getInformationLoss()` Returns the information loss
`InformationLoss<?>` Transformation.`getLowerBound()` Returns the lower bound on information loss
`InformationLoss<?>` SolutionSpaceLong.`getUtility(java.lang.Object _identifier)` Returns the utility of the transformation with the given identifier
`InformationLoss<?>` SolutionSpaceIntArray.`getUtility(java.lang.Object identifier)` Returns the utility of the transformation with the given identifier
`abstract InformationLoss<?>` SolutionSpace.`getUtility(java.lang.Object _identifier)` Returns the utility of the transformation with the given identifier

Methods in org.deidentifier.arx.framework.lattice with parameters of type InformationLoss
`void` Transformation.`setInformationLoss(InformationLoss<?> informationLoss)` Sets the information loss
`void` Transformation.`setLowerBound(InformationLoss<?> lowerBound)` Sets the lower bound

### Uses of InformationLoss in org.deidentifier.arx.metric

Classes in org.deidentifier.arx.metric with type parameters of type InformationLoss
`class` `InformationLossWithBound<T extends InformationLoss<?>>` Information loss with a potential lower bound.
`class` `Metric<T extends InformationLoss<?>>` Abstract base class for metrics.
`class` `MetricWeighted<T extends InformationLoss<?>>` This class provides an abstract skeleton for the implementation of weighted metrics.

Methods in org.deidentifier.arx.metric that return InformationLoss
`abstract InformationLoss<T>` InformationLoss.`clone()` Returns a clone of this object.
`static InformationLoss<?>` InformationLoss.`createInformationLoss(InformationLoss<?> loss, Metric<?> metric, int minLevel, int maxLevel)` Converter method, converting information loss from version 1 to information loss from version 2, if necessary.
`InformationLoss<?>` Metric.`createInstanceOfHighestScore()` Returns an instance of the highest possible score.
`InformationLoss<?>` Metric.`createInstanceOfLowestScore()` Returns an instance of the lowest possible score.
`InformationLoss<?>` MetricStatic.`createMaxInformationLoss()`
`InformationLoss<?>` MetricPrecision.`createMaxInformationLoss()`
`InformationLoss<?>` MetricNMPrecision.`createMaxInformationLoss()`
`InformationLoss<?>` MetricHeight.`createMaxInformationLoss()`
`InformationLoss<?>` MetricDMStar.`createMaxInformationLoss()`
`InformationLoss<?>` MetricDM.`createMaxInformationLoss()`
`InformationLoss<?>` MetricDefault.`createMaxInformationLoss()`
`InformationLoss<?>` MetricAECS.`createMaxInformationLoss()`
`abstract InformationLoss<?>` Metric.`createMaxInformationLoss()` Deprecated.
`InformationLoss<?>` MetricStatic.`createMinInformationLoss()`
`InformationLoss<?>` MetricPrecision.`createMinInformationLoss()`
`InformationLoss<?>` MetricNMPrecision.`createMinInformationLoss()`
`InformationLoss<?>` MetricHeight.`createMinInformationLoss()`
`InformationLoss<?>` MetricDMStar.`createMinInformationLoss()`
`InformationLoss<?>` MetricDM.`createMinInformationLoss()`
`InformationLoss<?>` MetricDefault.`createMinInformationLoss()`
`InformationLoss<?>` MetricAECS.`createMinInformationLoss()`
`abstract InformationLoss<?>` Metric.`createMinInformationLoss()` Deprecated.

Methods in org.deidentifier.arx.metric with parameters of type InformationLoss
`abstract int` InformationLoss.`compareTo(InformationLoss<?> other)` Compares the loss to the other.
`static InformationLoss<?>` InformationLoss.`createInformationLoss(InformationLoss<?> loss, Metric<?> metric, int minLevel, int maxLevel)` Converter method, converting information loss from version 1 to information loss from version 2, if necessary.
`abstract void` InformationLoss.`max(InformationLoss<?> other)` Retains the maximum of this and other.
`abstract void` InformationLoss.`min(InformationLoss<?> other)` Retains the minimum of this and other.
`abstract double` InformationLoss.`relativeTo(InformationLoss<?> min, InformationLoss<?> max)` Returns the value relative to the other instance.
`abstract double` InformationLoss.`relativeTo(InformationLoss<?> min, InformationLoss<?> max)` Returns the value relative to the other instance.

### Uses of InformationLoss in org.deidentifier.arx.metric.v2

Subclasses of InformationLoss in org.deidentifier.arx.metric.v2
`class` `AbstractILMultiDimensional` This class implements an information loss which can be represented as a decimal number per quasi-identifier.
`class` `AbstractILMultiDimensionalReduced` This class implements an information loss which can be represented as a decimal number per quasi-identifier.
`class` `ILMultiDimensionalArithmeticMean` This class implements an information loss which can be represented as a decimal number per quasi-identifier.
`class` `ILMultiDimensionalGeometricMean` This class implements an information loss which can be represented as a decimal number per quasi-identifier.
`class` `ILMultiDimensionalMax` This class implements an information loss which can be represented as a decimal number per quasi-identifier.
`class` `ILMultiDimensionalRank` This class implements an information loss which can be represented as a decimal number per quasi-identifier.
`class` `ILMultiDimensionalSum` This class implements an information loss which can be represented as a decimal number per quasi-identifier.
`class` `ILScore` This class implements information loss using score values for data-independent differential privacy with appropriate comparison semantics (i.e. higher score values are better).
`class` `ILSingleDimensional` This class implements an information loss which can be represented as a single decimal number.

Methods in org.deidentifier.arx.metric.v2 that return InformationLoss
`InformationLoss<java.lang.Double>` ILSingleDimensional.`clone()`
`InformationLoss<org.apache.commons.math3.fraction.BigFraction>` ILScore.`clone()`
`InformationLoss<double[]>` ILMultiDimensionalSum.`clone()`
`InformationLoss<double[]>` ILMultiDimensionalRank.`clone()`
`InformationLoss<double[]>` ILMultiDimensionalMax.`clone()`
`InformationLoss<double[]>` ILMultiDimensionalGeometricMean.`clone()`
`InformationLoss<double[]>` ILMultiDimensionalArithmeticMean.`clone()`
`abstract InformationLoss<double[]>` AbstractILMultiDimensionalReduced.`clone()` Override this to implement a variant.
`abstract InformationLoss<double[]>` AbstractILMultiDimensional.`clone()`
`static InformationLoss<?>` __MetricV2.`createILMultiDimensionalArithmeticMean(double value)` Helper method.
`static InformationLoss<?>` __MetricV2.`createILMultiDimensionalSum(double value)` Helper method.
`static InformationLoss<?>` __MetricV2.`createILSingleDimensional(double value)` Helper method.
`InformationLoss<?>` AbstractMetricSingleDimensional.`createMaxInformationLoss()`
`InformationLoss<?>` AbstractMetricMultiDimensionalPotentiallyPrecomputed.`createMaxInformationLoss()`
`InformationLoss<?>` AbstractMetricMultiDimensional.`createMaxInformationLoss()`
`InformationLoss<?>` AbstractMetricSingleDimensional.`createMinInformationLoss()`
`InformationLoss<?>` AbstractMetricMultiDimensionalPotentiallyPrecomputed.`createMinInformationLoss()`
`InformationLoss<?>` AbstractMetricMultiDimensional.`createMinInformationLoss()`

Methods in org.deidentifier.arx.metric.v2 with parameters of type InformationLoss
`int` ILSingleDimensional.`compareTo(InformationLoss<?> other)`
`int` ILScore.`compareTo(InformationLoss<?> other)`
`int` ILMultiDimensionalRank.`compareTo(InformationLoss<?> other)`
`int` AbstractILMultiDimensionalReduced.`compareTo(InformationLoss<?> other)`
`abstract int` AbstractILMultiDimensional.`compareTo(InformationLoss<?> other)`
`void` ILSingleDimensional.`max(InformationLoss<?> other)`
`void` ILScore.`max(InformationLoss<?> other)`
`void` AbstractILMultiDimensional.`max(InformationLoss<?> other)`
`void` ILSingleDimensional.`min(InformationLoss<?> other)`
`void` ILScore.`min(InformationLoss<?> other)`
`void` AbstractILMultiDimensional.`min(InformationLoss<?> other)`
`double` ILSingleDimensional.`relativeTo(InformationLoss<?> min, InformationLoss<?> max)`
`double` ILSingleDimensional.`relativeTo(InformationLoss<?> min, InformationLoss<?> max)`
`double` ILScore.`relativeTo(InformationLoss<?> min, InformationLoss<?> max)`
`double` ILScore.`relativeTo(InformationLoss<?> min, InformationLoss<?> max)`
`double` ILMultiDimensionalRank.`relativeTo(InformationLoss<?> min, InformationLoss<?> max)`
`double` ILMultiDimensionalRank.`relativeTo(InformationLoss<?> min, InformationLoss<?> max)`
`double` AbstractILMultiDimensionalReduced.`relativeTo(InformationLoss<?> min, InformationLoss<?> max)`
`double` AbstractILMultiDimensionalReduced.`relativeTo(InformationLoss<?> min, InformationLoss<?> max)`
`abstract double` AbstractILMultiDimensional.`relativeTo(InformationLoss<?> min, InformationLoss<?> max)`
`abstract double` AbstractILMultiDimensional.`relativeTo(InformationLoss<?> min, InformationLoss<?> max)`