## Uses of Class
org.deidentifier.arx.metric.Metric.AggregateFunction

Packages that use Metric.AggregateFunction
org.deidentifier.arx.metric: Package providing access to quality models
org.deidentifier.arx.metric.v2: Main package implementing quality models

### Uses of Metric.AggregateFunction in org.deidentifier.arx.metric

Methods in org.deidentifier.arx.metric that return Metric.AggregateFunction
`Metric.AggregateFunction` MetricConfiguration.`getAggregateFunction()`
`Metric.AggregateFunction` Metric.`getAggregateFunction()` Returns the aggregate function of a multi-dimensional metric, null otherwise.
`static Metric.AggregateFunction` Metric.AggregateFunction.`valueOf(java.lang.String name)` Returns the enum constant of this type with the specified name.
`static Metric.AggregateFunction[]` Metric.AggregateFunction.`values()` Returns an array containing the constants of this enum type, in the order they are declared.

Methods in org.deidentifier.arx.metric that return types with arguments of type Metric.AggregateFunction
`java.util.List<Metric.AggregateFunction>` MetricDescription.`getSupportedAggregateFunctions()` Returns a list of all supported aggregate functions.

Methods in org.deidentifier.arx.metric with parameters of type Metric.AggregateFunction
`static Metric<AbstractILMultiDimensional>` Metric.`createEntropyMetric(boolean monotonic, double gsFactor, Metric.AggregateFunction function)` Creates an instance of the non-uniform entropy metric.
`static Metric<AbstractILMultiDimensional>` Metric.`createEntropyMetric(boolean monotonic, Metric.AggregateFunction function)` Creates an instance of the non-uniform entropy metric.
`static Metric<AbstractILMultiDimensional>` Metric.`createHeightMetric(Metric.AggregateFunction function)` Creates an instance of the height metric.
`static Metric<AbstractILMultiDimensional>` Metric.`createLossMetric(double gsFactor, Metric.AggregateFunction function)` Creates an instance of the loss metric with factors for weighting generalization and suppression.
`static Metric<AbstractILMultiDimensional>` Metric.`createLossMetric(Metric.AggregateFunction function)` Creates an instance of the loss metric which treats generalization and suppression equally.
`static Metric<AbstractILMultiDimensional>` Metric.`createNormalizedEntropyMetric(Metric.AggregateFunction function)` Creates an instance of the normalized entropy metric.
`static Metric<AbstractILMultiDimensional>` Metric.`createPrecisionMetric(boolean monotonic, double gsFactor, Metric.AggregateFunction function)` Creates an instance of the precision metric.
`static Metric<AbstractILMultiDimensional>` Metric.`createPrecisionMetric(boolean monotonic, Metric.AggregateFunction function)` Creates an instance of the precision metric.
`static Metric<AbstractILMultiDimensional>` Metric.`createPrecisionMetric(double gsFactor, Metric.AggregateFunction function)` Creates an instance of the non-monotonic precision metric.
`static Metric<AbstractILMultiDimensional>` Metric.`createPrecisionMetric(Metric.AggregateFunction function)` Creates an instance of the non-monotonic precision metric.
`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.
`static Metric<AbstractILMultiDimensional>` Metric.`createPrecomputedEntropyMetric(double threshold, boolean monotonic, Metric.AggregateFunction function)` Creates a potentially precomputed instance of the non-uniform entropy metric.
`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.
`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.
`static Metric<AbstractILMultiDimensional>` Metric.`createPrecomputedNormalizedEntropyMetric(double threshold, Metric.AggregateFunction function)` Creates a potentially precomputed instance of the normalized entropy metric.
`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.
`void` MetricConfiguration.`setAggregateFunction(Metric.AggregateFunction aggregateFunction)`

Constructors in org.deidentifier.arx.metric with parameters of type Metric.AggregateFunction
Constructor and Description
`MetricConfiguration(boolean monotonic, double gsFactor, boolean precomputed, double precomputationThreshold, Metric.AggregateFunction aggregateFunction)` Constructs a new instance.

### Uses of Metric.AggregateFunction in org.deidentifier.arx.metric.v2

Methods in org.deidentifier.arx.metric.v2 that return Metric.AggregateFunction
`Metric.AggregateFunction` AbstractMetricMultiDimensionalPotentiallyPrecomputed.`getAggregateFunction()`
`Metric.AggregateFunction` AbstractMetricMultiDimensional.`getAggregateFunction()`

Methods in org.deidentifier.arx.metric.v2 with parameters of type Metric.AggregateFunction
`static Metric<AbstractILMultiDimensional>` __MetricV2.`createEntropyMetric(boolean monotonic, double gsFactor, Metric.AggregateFunction function)` Creates an instance of the non-uniform entropy metric.
`static Metric<AbstractILMultiDimensional>` __MetricV2.`createEntropyMetric(boolean monotonic, Metric.AggregateFunction function)` Creates an instance of the non-uniform entropy metric.
`static Metric<AbstractILMultiDimensional>` __MetricV2.`createHeightMetric(Metric.AggregateFunction function)` Creates an instance of the height metric.
`static Metric<AbstractILMultiDimensional>` __MetricV2.`createLossMetric(double gsFactor, Metric.AggregateFunction function)` Creates an instance of the loss metric with factors for weighting generalization and suppression.
`static Metric<AbstractILMultiDimensional>` __MetricV2.`createLossMetric(Metric.AggregateFunction function)` Creates an instance of the loss metric which treats generalization and suppression equally.
`static Metric<AbstractILMultiDimensional>` __MetricV2.`createNormalizedEntropyMetric(Metric.AggregateFunction function)` Creates an instance of the normalized entropy metric.
`static Metric<AbstractILMultiDimensional>` __MetricV2.`createPrecisionMetric(boolean monotonic, double gsFactor, Metric.AggregateFunction function)` Creates an instance of the precision metric.
`static Metric<AbstractILMultiDimensional>` __MetricV2.`createPrecisionMetric(boolean monotonic, Metric.AggregateFunction function)` Creates an instance of the precision metric.
`static Metric<AbstractILMultiDimensional>` __MetricV2.`createPrecisionMetric(double gsFactor, Metric.AggregateFunction function)` Creates an instance of the non-monotonic precision metric.
`static Metric<AbstractILMultiDimensional>` __MetricV2.`createPrecisionMetric(Metric.AggregateFunction function)` Creates an instance of the non-monotonic precision metric.
`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.
`static Metric<AbstractILMultiDimensional>` __MetricV2.`createPrecomputedEntropyMetric(double threshold, boolean monotonic, Metric.AggregateFunction function)` Creates a potentially precomputed instance of the non-uniform entropy metric.
`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.
`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.
`static Metric<AbstractILMultiDimensional>` __MetricV2.`createPrecomputedNormalizedEntropyMetric(double threshold, Metric.AggregateFunction function)` Creates a potentially precomputed instance of the normalized entropy metric.
`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.

Constructors in org.deidentifier.arx.metric.v2 with parameters of type Metric.AggregateFunction
Constructor and Description
`MetricMDNMLoss(double gsFactor, Metric.AggregateFunction function)` A constructor that allows to define a factor weighting generalization and suppression.
`MetricMDNMLoss(Metric.AggregateFunction function)` Default constructor which treats all transformation methods equally.
`MetricMDNUEntropyPrecomputed(boolean monotonicWithGeneralization, boolean monotonicWithSuppression, boolean independent, double gsFactor, Metric.AggregateFunction function)` Precomputed.
`MetricMDNUNMNormalizedEntropyPrecomputed(Metric.AggregateFunction function)` Creates a new instance.