Package | Description |
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org.deidentifier.arx.metric |
Package providing access to quality models
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org.deidentifier.arx.metric.v2 |
Main package implementing quality models
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Modifier and Type | Method and Description |
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Metric.AggregateFunction |
MetricConfiguration.getAggregateFunction() |
Metric.AggregateFunction |
Metric.getAggregateFunction()
Returns the aggregate function of a multi-dimensional metric, null otherwise.
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static Metric.AggregateFunction |
Metric.AggregateFunction.valueOf(java.lang.String name)
Returns the enum constant of this type with the specified name.
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static Metric.AggregateFunction[] |
Metric.AggregateFunction.values()
Returns an array containing the constants of this enum type, in
the order they are declared.
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Modifier and Type | Method and Description |
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java.util.List<Metric.AggregateFunction> |
MetricDescription.getSupportedAggregateFunctions()
Returns a list of all supported aggregate functions.
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Modifier and Type | Method and Description |
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static Metric<AbstractILMultiDimensional> |
Metric.createEntropyMetric(boolean monotonic,
double gsFactor,
Metric.AggregateFunction function)
Creates an instance of the non-uniform entropy metric.
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static Metric<AbstractILMultiDimensional> |
Metric.createEntropyMetric(boolean monotonic,
Metric.AggregateFunction function)
Creates an instance of the non-uniform entropy metric.
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static Metric<AbstractILMultiDimensional> |
Metric.createHeightMetric(Metric.AggregateFunction function)
Creates an instance of the height metric.
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static Metric<AbstractILMultiDimensional> |
Metric.createLossMetric(double gsFactor,
Metric.AggregateFunction function)
Creates an instance of the loss metric with factors for weighting generalization and suppression.
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static Metric<AbstractILMultiDimensional> |
Metric.createLossMetric(Metric.AggregateFunction function)
Creates an instance of the loss metric which treats generalization and suppression equally.
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static Metric<AbstractILMultiDimensional> |
Metric.createNormalizedEntropyMetric(Metric.AggregateFunction function)
Creates an instance of the normalized entropy metric.
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static Metric<AbstractILMultiDimensional> |
Metric.createPrecisionMetric(boolean monotonic,
double gsFactor,
Metric.AggregateFunction function)
Creates an instance of the precision metric.
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static Metric<AbstractILMultiDimensional> |
Metric.createPrecisionMetric(boolean monotonic,
Metric.AggregateFunction function)
Creates an instance of the precision metric.
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static Metric<AbstractILMultiDimensional> |
Metric.createPrecisionMetric(double gsFactor,
Metric.AggregateFunction function)
Creates an instance of the non-monotonic precision metric.
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static Metric<AbstractILMultiDimensional> |
Metric.createPrecisionMetric(Metric.AggregateFunction function)
Creates an instance of the non-monotonic precision metric.
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static Metric<AbstractILMultiDimensional> |
Metric.createPrecomputedEntropyMetric(double threshold,
boolean monotonic,
double gsFactor,
Metric.AggregateFunction function)
Creates a potentially precomputed instance of the non-uniform entropy metric.
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static Metric<AbstractILMultiDimensional> |
Metric.createPrecomputedEntropyMetric(double threshold,
boolean monotonic,
Metric.AggregateFunction function)
Creates a potentially precomputed instance of the non-uniform entropy metric.
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static Metric<AbstractILMultiDimensional> |
Metric.createPrecomputedLossMetric(double threshold,
double gsFactor,
Metric.AggregateFunction function)
Creates a potentially precomputed instance of the loss metric with factors for weighting generalization and suppression.
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static Metric<AbstractILMultiDimensional> |
Metric.createPrecomputedLossMetric(double threshold,
Metric.AggregateFunction function)
Creates a potentially precomputed instance of the loss metric which treats generalization and suppression equally.
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static Metric<AbstractILMultiDimensional> |
Metric.createPrecomputedNormalizedEntropyMetric(double threshold,
Metric.AggregateFunction function)
Creates a potentially precomputed instance of the normalized entropy metric.
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static Metric<AbstractILMultiDimensional> |
Metric.createStaticMetric(java.util.Map<java.lang.String,java.util.List<java.lang.Double>> loss,
Metric.AggregateFunction function)
Creates an instance of a metric with statically defined information loss.
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void |
MetricConfiguration.setAggregateFunction(Metric.AggregateFunction aggregateFunction) |
Constructor and Description |
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MetricConfiguration(boolean monotonic,
double gsFactor,
boolean precomputed,
double precomputationThreshold,
Metric.AggregateFunction aggregateFunction)
Constructs a new instance.
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Modifier and Type | Method and Description |
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Metric.AggregateFunction |
AbstractMetricMultiDimensionalPotentiallyPrecomputed.getAggregateFunction() |
Metric.AggregateFunction |
AbstractMetricMultiDimensional.getAggregateFunction() |
Modifier and Type | Method and Description |
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static Metric<AbstractILMultiDimensional> |
__MetricV2.createEntropyMetric(boolean monotonic,
double gsFactor,
Metric.AggregateFunction function)
Creates an instance of the non-uniform entropy metric.
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static Metric<AbstractILMultiDimensional> |
__MetricV2.createEntropyMetric(boolean monotonic,
Metric.AggregateFunction function)
Creates an instance of the non-uniform entropy metric.
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static Metric<AbstractILMultiDimensional> |
__MetricV2.createHeightMetric(Metric.AggregateFunction function)
Creates an instance of the height metric.
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static Metric<AbstractILMultiDimensional> |
__MetricV2.createLossMetric(double gsFactor,
Metric.AggregateFunction function)
Creates an instance of the loss metric with factors for weighting generalization and suppression.
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static Metric<AbstractILMultiDimensional> |
__MetricV2.createLossMetric(Metric.AggregateFunction function)
Creates an instance of the loss metric which treats generalization and suppression equally.
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static Metric<AbstractILMultiDimensional> |
__MetricV2.createNormalizedEntropyMetric(Metric.AggregateFunction function)
Creates an instance of the normalized entropy metric.
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static Metric<AbstractILMultiDimensional> |
__MetricV2.createPrecisionMetric(boolean monotonic,
double gsFactor,
Metric.AggregateFunction function)
Creates an instance of the precision metric.
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static Metric<AbstractILMultiDimensional> |
__MetricV2.createPrecisionMetric(boolean monotonic,
Metric.AggregateFunction function)
Creates an instance of the precision metric.
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static Metric<AbstractILMultiDimensional> |
__MetricV2.createPrecisionMetric(double gsFactor,
Metric.AggregateFunction function)
Creates an instance of the non-monotonic precision metric.
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static Metric<AbstractILMultiDimensional> |
__MetricV2.createPrecisionMetric(Metric.AggregateFunction function)
Creates an instance of the non-monotonic precision metric.
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static Metric<AbstractILMultiDimensional> |
__MetricV2.createPrecomputedEntropyMetric(double threshold,
boolean monotonic,
double gsFactor,
Metric.AggregateFunction function)
Creates a potentially precomputed instance of the non-uniform entropy metric.
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static Metric<AbstractILMultiDimensional> |
__MetricV2.createPrecomputedEntropyMetric(double threshold,
boolean monotonic,
Metric.AggregateFunction function)
Creates a potentially precomputed instance of the non-uniform entropy metric.
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static Metric<AbstractILMultiDimensional> |
__MetricV2.createPrecomputedLossMetric(double threshold,
double gsFactor,
Metric.AggregateFunction function)
Creates a potentially precomputed instance of the loss metric with factors for weighting generalization and suppression.
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static Metric<AbstractILMultiDimensional> |
__MetricV2.createPrecomputedLossMetric(double threshold,
Metric.AggregateFunction function)
Creates a potentially precomputed instance of the loss metric which treats generalization and suppression equally.
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static Metric<AbstractILMultiDimensional> |
__MetricV2.createPrecomputedNormalizedEntropyMetric(double threshold,
Metric.AggregateFunction function)
Creates a potentially precomputed instance of the normalized entropy metric.
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static Metric<AbstractILMultiDimensional> |
__MetricV2.createStaticMetric(java.util.Map<java.lang.String,java.util.List<java.lang.Double>> loss,
Metric.AggregateFunction function)
Creates an instance of a metric with statically defined information loss.
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Constructor and Description |
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MetricMDNMLoss(double gsFactor,
Metric.AggregateFunction function)
A constructor that allows to define a factor weighting generalization and suppression.
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MetricMDNMLoss(Metric.AggregateFunction function)
Default constructor which treats all transformation methods equally.
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MetricMDNUEntropyPrecomputed(boolean monotonicWithGeneralization,
boolean monotonicWithSuppression,
boolean independent,
double gsFactor,
Metric.AggregateFunction function)
Precomputed.
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MetricMDNUNMNormalizedEntropyPrecomputed(Metric.AggregateFunction function)
Creates a new instance.
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