# Package org.deidentifier.arx.aggregates.quality

This package provides implementations of various quality models which can be used for quality analysis (but not as optimization functions)

See: Description

Interface Summary
QualityDomainShare: Base class for representing domain shares in this package

Class Summary
QualityAggregateFunction: Aggregate function for multi-dimensional quality measures
QualityConfiguration: Basic configuration for quality models
QualityConfigurationRangeParser: Parser for ranges
QualityDomainShareRaw: Raw domain-share (unencoded).
QualityDomainShareRedaction: This class represents a set of domain shares for an attribute.
QualityMeasure: Base class for quality measures.
QualityMeasureColumnOriented: Quality measures for individual attributes.
QualityMeasureRowOriented: A measure for the complete dataset.
QualityModelColumnOrientedLoss: Implementation of the Loss measure, as proposed in: Iyengar, V.: Transforming data to satisfy privacy constraints.
QualityModelColumnOrientedNonUniformEntropy: Implementation of the Non-Uniform Entropy measure that can handle local recoding.
QualityModelColumnOrientedPrecision: Implementation of the Precision measure, as proposed in: L.
QualityModelColumnOrientedSquaredError: Implementation of the mean squared error for individual columns
QualityModelRowOrientedAECS: Implementation of the AECS measure, as proposed in: K.
QualityModelRowOrientedAmbiguity: Implementation of the Ambiguity measure, as described in: Goldberger, Tassa: "Efficient Anonymizations with Enhanced Utility" Trans Data Priv
QualityModelRowOrientedDiscernibility: Implementation of the Discernibility measure, as proposed in: R.
QualityModelRowOrientedSquaredError: Implementation of the Sum of Squared Errors introduced in the supplementary material to: D.
QualityModelRowOrientedSSESST: SSE / SST as described in Solanas, Agusti, Antoni Martinez-Balleste, and J.

## Package org.deidentifier.arx.aggregates.quality Description

This package provides implementations of various quality models which can be used for quality analysis (but not as optimization functions)

Author:
  Fabian Prasser