Package | Description |
---|---|
org.deidentifier.arx |
This package provides the public API for the ARX anonymization framework.
|
org.deidentifier.arx.metric |
This package implements several metrics for information loss.
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org.deidentifier.arx.metric.v2 |
Modifier and Type | Method and Description |
---|---|
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<?> |
ARXLattice.getMaximumInformationLoss()
Deprecated.
|
InformationLoss<?> |
ARXLattice.ARXNode.getMaximumInformationLoss()
Deprecated.
|
InformationLoss<?> |
ARXLattice.getMinimumInformationLoss()
Deprecated.
|
InformationLoss<?> |
ARXLattice.ARXNode.getMinimumInformationLoss()
Deprecated.
|
Modifier and Type | Method and Description |
---|---|
void |
ARXLattice.ARXNode.Access.setHighestScore(InformationLoss<?> a)
Sets the maximal information loss.
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void |
ARXLattice.ARXNode.Access.setLowerBound(InformationLoss<?> a)
Sets the lower bound.
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void |
ARXLattice.ARXNode.Access.setLowestScore(InformationLoss<?> a)
Sets the minimal information loss.
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Modifier and Type | Class and Description |
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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.
|
Modifier and Type | Method and Description |
---|---|
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.
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abstract void |
InformationLoss.min(InformationLoss<?> other)
Retains the minimum of this and other.
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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.
|
Modifier and Type | Class and Description |
---|---|
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 |
ILSingleDimensional
This class implements an information loss which can be represented as a
single decimal number.
|
Modifier and Type | Method and Description |
---|---|
InformationLoss<double[]> |
ILMultiDimensionalRank.clone() |
InformationLoss<double[]> |
ILMultiDimensionalGeometricMean.clone() |
abstract InformationLoss<double[]> |
AbstractILMultiDimensional.clone() |
InformationLoss<double[]> |
ILMultiDimensionalArithmeticMean.clone() |
abstract InformationLoss<double[]> |
AbstractILMultiDimensionalReduced.clone()
Override this to implement a variant.
|
InformationLoss<java.lang.Double> |
ILSingleDimensional.clone() |
InformationLoss<double[]> |
ILMultiDimensionalMax.clone() |
InformationLoss<double[]> |
ILMultiDimensionalSum.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<?> |
AbstractMetricMultiDimensional.createMaxInformationLoss() |
InformationLoss<?> |
AbstractMetricMultiDimensionalPotentiallyPrecomputed.createMaxInformationLoss() |
InformationLoss<?> |
AbstractMetricSingleDimensional.createMinInformationLoss() |
InformationLoss<?> |
AbstractMetricMultiDimensional.createMinInformationLoss() |
InformationLoss<?> |
AbstractMetricMultiDimensionalPotentiallyPrecomputed.createMinInformationLoss() |
Modifier and Type | Method and Description |
---|---|
int |
ILMultiDimensionalRank.compareTo(InformationLoss<?> other) |
abstract int |
AbstractILMultiDimensional.compareTo(InformationLoss<?> other) |
int |
AbstractILMultiDimensionalReduced.compareTo(InformationLoss<?> other) |
int |
ILSingleDimensional.compareTo(InformationLoss<?> other) |
void |
AbstractILMultiDimensional.max(InformationLoss<?> other) |
void |
ILSingleDimensional.max(InformationLoss<?> other) |
void |
AbstractILMultiDimensional.min(InformationLoss<?> other) |
void |
ILSingleDimensional.min(InformationLoss<?> other) |
double |
ILMultiDimensionalRank.relativeTo(InformationLoss<?> min,
InformationLoss<?> max) |
double |
ILMultiDimensionalRank.relativeTo(InformationLoss<?> min,
InformationLoss<?> max) |
abstract double |
AbstractILMultiDimensional.relativeTo(InformationLoss<?> min,
InformationLoss<?> max) |
abstract double |
AbstractILMultiDimensional.relativeTo(InformationLoss<?> min,
InformationLoss<?> max) |
double |
AbstractILMultiDimensionalReduced.relativeTo(InformationLoss<?> min,
InformationLoss<?> max) |
double |
AbstractILMultiDimensionalReduced.relativeTo(InformationLoss<?> min,
InformationLoss<?> max) |
double |
ILSingleDimensional.relativeTo(InformationLoss<?> min,
InformationLoss<?> max) |
double |
ILSingleDimensional.relativeTo(InformationLoss<?> min,
InformationLoss<?> max) |