# Package org.deidentifier.arx.aggregates

This package provides methods for aggregating data: (1) builders for generalization hierarchies, (2) various methods for analyzing data quality and utility

See: Description

Class Summary
AggregateFunction<T>: This abstract class represents an aggregate function.
AggregateFunction.AggregateFunctionBuilder<T>: A builder for aggregate functions.
AggregateFunction.AggregateFunctionWithParameter<T>: An aggregate function that has a parameter.
AggregateFunction.GenericArithmeticMean<T>: An aggregate function that returns the arithmetic mean, if it may be computed, "NULL" otherwise.
AggregateFunction.GenericArithmeticMeanOfBounds<T>: An aggregate function that returns the arithmetic mean of min & max, if it may be computed, "NULL" otherwise.
AggregateFunction.GenericBounds<T>: An aggregate function that returns an interval consisting of the first and the last element following the predefined order .
AggregateFunction.GenericCommonPrefix<T>: An aggregate function that returns a common prefix.
AggregateFunction.GenericConstant<T>: An aggregate function that returns a constant value.
AggregateFunction.GenericGeometricMean<T>: An aggregate function that returns the geometric mean, if it may be computed, "NULL" otherwise.
AggregateFunction.GenericGeometricMeanOfBounds<T>: An aggregate function that returns the geometric mean of min & max, if it may be computed, "NULL" otherwise.
AggregateFunction.GenericInterval<T>: An aggregate function that returns an interval [min, max] .
AggregateFunction.GenericSet<T>: An aggregate function that returns a set of all data values.
AggregateFunction.GenericSetOfPrefixes<T>: An aggregate function that returns a set of the prefixes of the data values.
ClassificationConfigurationLogisticRegression: Configuration for logistic regression
ClassificationConfigurationNaiveBayes: Configuration for naive bayes classification
ClassificationConfigurationRandomForest: Configuration for Random Forest classifiers
HierarchyBuilder<T>: Base class for hierarchy builders.
HierarchyBuilderDate: This class enables building hierarchies for dates.
HierarchyBuilderDate.Format: A format-class for localization
HierarchyBuilderGroupingBased<T>: This abstract base class enables building hierarchies for categorical and non-categorical values.
HierarchyBuilderGroupingBased.Group<U>: This class represents a fanout parameter.
HierarchyBuilderGroupingBased.Level<U>: This class represents a level in the hierarchy.
HierarchyBuilderIntervalBased<T>: This class enables building hierarchies for non-categorical values by mapping them into given intervals.
HierarchyBuilderIntervalBased.Interval<T>: This class represents an interval.
HierarchyBuilderIntervalBased.Range<U>: For each direction, this class encapsulates three bounds.
HierarchyBuilderOrderBased<T>: This class enables building hierarchies for categorical and non-categorical values by ordering the data items and merging into groups with predefined sizes.
HierarchyBuilderOrderBased.SerializableComparator<T>: A serializable comparator.
HierarchyBuilderRedactionBased<T>: This class enables building hierarchies for categorical and non-categorical values using redaction.
StatisticsBuilder: A class offering basic descriptive statistics about data handles.
StatisticsBuilderInterruptible: A class offering basic descriptive statistics about data handles.
StatisticsClassification: Statistics representing the performance of various classifiers
StatisticsClassification.ROCCurve: A ROC curve
StatisticsContingencyTable: A contingency table.
StatisticsContingencyTable.Entry: An entry in the contingency table.
StatisticsEquivalenceClasses: Statistics about the equivalence classes.
StatisticsFrequencyDistribution: A frequency distribution.
StatisticsQuality: Encapsulates statistics obtained using various quality models
StatisticsSummary<T>: A base class for summary statistics

Enum Summary
ClassificationConfigurationLogisticRegression.PriorFunction: Prior function for regularization
ClassificationConfigurationNaiveBayes.Type: Type of bayes classifier
ClassificationConfigurationRandomForest.SplitRule: Split rule for the decision tree
HierarchyBuilder.Type: The three types of builders.
HierarchyBuilderDate.Granularity: Granularity
HierarchyBuilderRedactionBased.Order: Order

## Package org.deidentifier.arx.aggregates Description

This package provides methods for aggregating data: (1) builders for generalization hierarchies, (2) various methods for analyzing data quality and utility

Author:
  Fabian Prasser, Florian Kohlmayer