# org.deidentifier.arx.metric.v2 (ARX GUI Documentation)

# Package org.deidentifier.arx.metric.v2

- Interface Summary
  Interface | Description
  --- | ---
  DomainShare | Base interface for domain shares.

- Class Summary
  Class | Description
  --- | ---
  __MetricV2 | This internal class provides access to version 2 of all metrics.
  AbstractILMultiDimensional | This class implements an information loss which can be represented as a decimal number per quasi-identifier.
  AbstractILMultiDimensionalReduced | This class implements an information loss which can be represented as a decimal number per quasi-identifier.
  AbstractMetricMultiDimensional | This class provides an abstract skeleton for the implementation of multi-dimensional metrics.
  AbstractMetricMultiDimensionalPotentiallyPrecomputed | This class provides an abstract skeleton for the implementation of metrics that can either be precomputed or not.
  AbstractMetricSingleDimensional | This class provides an abstract skeleton for the implementation of single-dimensional metrics.
  Cardinalities | This class represents cardinalities.
  DomainShareInterval<T> | This class represents a set of domain shares for an attribute.
  DomainShareMaterialized | This class represents a set of domain shares for an attribute.
  DomainShareRedaction | This class represents a set of domain shares for an attribute.
  ILMultiDimensionalArithmeticMean | This class implements an information loss which can be represented as a decimal number per quasi-identifier.
  ILMultiDimensionalGeometricMean | This class implements an information loss which can be represented as a decimal number per quasi-identifier.
  ILMultiDimensionalMax | This class implements an information loss which can be represented as a decimal number per quasi-identifier.
  ILMultiDimensionalRank | This class implements an information loss which can be represented as a decimal number per quasi-identifier.
  ILMultiDimensionalSum | This class implements an information loss which can be represented as a decimal number per quasi-identifier.
  ILMultiDimensionalWithBound | Information loss with a potential lower bound.
  ILSingleDimensional | This class implements an information loss which can be represented as a single decimal number.
  ILSingleDimensionalWithBound | Information loss with a potential lower bound.
  IO |
  MetricMDHeight | This class provides an implementation of the Height metric.
  MetricMDNMLoss | This class implements a variant of the Loss metric.
  MetricMDNMLossPotentiallyPrecomputed | This class implements a variant of the Loss metric.
  MetricMDNMLossPrecomputed | This class implements a variant of the Loss metric.
  MetricMDNMPrecision | This class provides an implementation of a weighted precision metric as proposed in: Sweeney, L.
  MetricMDNUEntropy | This class provides an implementation of the non-uniform entropy metric.
  MetricMDNUEntropyPotentiallyPrecomputed | This class provides an implementation of the non-uniform entropy metric.
  MetricMDNUEntropyPrecomputed | This class provides an efficient implementation of the non-uniform entropy metric.
  MetricMDNUNMEntropy | This class provides an implementation of the non-uniform entropy metric.
  MetricMDNUNMEntropyPotentiallyPrecomputed | This class provides an implementation of the non-uniform entropy metric.
  MetricMDNUNMEntropyPrecomputed | This class provides an implementation of the non-uniform entropy metric.
  MetricMDNUNMNormalizedEntropy | This class provides an implementation of normalized non-uniform entropy
  MetricMDNUNMNormalizedEntropyPotentiallyPrecomputed | This class provides an implementation of normalized non-uniform entropy
  MetricMDNUNMNormalizedEntropyPrecomputed | This class provides an efficient implementation of normalized non-uniform entropy
  MetricMDPrecision | This class provides an implementation of a weighted precision metric as proposed in: Sweeney, L.
  MetricMDStatic | This class provides an implementation of a static metric in which information loss is user-defined per generalization level.
  MetricSDAECS | This class provides an implementation of the (normalized) average equivalence class size metric.
  MetricSDDiscernability | This class provides an implementation of the monotonic DM* metric.
  MetricSDNMAmbiguity | This class implements a variant of the Ambiguity metric.
  MetricSDNMDiscernability | This class provides an implementation of the non-monotonic DM metric.
  MetricSDNMEntropyBasedInformationLoss | This class implements a the entropy-based information loss model proposed in: A Game Theoretic Framework for Analyzing Re-Identification Risk.
  MetricSDNMKLDivergence | This class implements the KL Divergence metric.
  MetricSDNMPublisherPayout | This class implements a model which maximizes publisher benefit according to the model proposed in: A Game Theoretic Framework for Analyzing Re-Identification Risk.
  QualityMetadata<T> | A class encapsulating information about data quality
  TupleMatcher | A class that supports associating input with output