Class | Description |
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InformationLoss<T> |
This class implements an abstract base class for information loss.
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InformationLossDefaultWithBound |
Information loss with a potential lower bound.
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InformationLossWithBound<T extends InformationLoss<?>> |
Information loss with a potential lower bound.
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Metric<T extends InformationLoss<?>> |
Abstract base class for metrics.
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MetricAECS |
This class provides an implementation of the (normalized) average equivalence class size metric.
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MetricConfiguration |
A class for a configuration of a metric.
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MetricDefault |
This class provides an abstract skeleton for the implementation of metrics.
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MetricDescription |
A class describing a metric and its configuration options.
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MetricDM |
This class provides an implementation of the DM metric (non-monotonic).
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MetricDMStar |
This class provides an implementation of the DM* metric (monotonic variant of
the Discernability Metric).
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MetricEntropy |
This class provides an efficient implementation of the non-uniform entropy
metric.
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MetricHeight |
This class provides an implementation of the Height metric.
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MetricNMEntropy |
This class provides an efficient implementation of a non-monotonic and
non-uniform entropy metric.
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MetricNMPrecision |
This class provides an implementation of a weighted precision metric as
proposed in:
Sweeney, L. (2002). |
MetricPrecision |
This class provides an implementation of a monotonic weighted precision metric.
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MetricStatic |
This class provides an implementation of a static metric in
which information loss is user-defined per generalization level.
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MetricWeighted<T extends InformationLoss<?>> |
This class provides an abstract skeleton for the implementation of weighted metrics.
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Enum | Description |
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Metric.AggregateFunction |
Pluggable aggregate functions.
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