Uses of Class
org.tribuo.util.infotheory.impl.WeightCountTuple
Packages that use WeightCountTuple
Package
Description
This package provides static classes of information theoretic functions.
This package provides the implementations and helper classes for the
information theoretic functions in
org.tribuo.util.infotheory
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Uses of WeightCountTuple in org.tribuo.util.infotheory
Methods in org.tribuo.util.infotheory that return types with arguments of type WeightCountTupleModifier and TypeMethodDescriptionstatic <T> Map<T,
WeightCountTuple> WeightedInformationTheory.calculateWeightedCountDist
(ArrayList<T> vector, ArrayList<Double> weights) Generate the counts for a single vector.Method parameters in org.tribuo.util.infotheory with type arguments of type WeightCountTupleModifier and TypeMethodDescriptionstatic <T> void
WeightedInformationTheory.normaliseWeights
(Map<T, WeightCountTuple> map) Normalizes the weights in the map, i.e., divides each weight by it's count. -
Uses of WeightCountTuple in org.tribuo.util.infotheory.impl
Methods in org.tribuo.util.infotheory.impl that return types with arguments of type WeightCountTupleModifier and TypeMethodDescriptionWeightedTripleDistribution.getABCount()
The joint distribution over the first and second variables.WeightedTripleDistribution.getACCount()
The joint distribution over the first and third variables.WeightedTripleDistribution.getACount()
The marginal distribution over the first variable.WeightedTripleDistribution.getBCCount()
The joint distribution over the second and third variables.WeightedTripleDistribution.getBCount()
The marginal distribution over the second variable.WeightedTripleDistribution.getCCount()
The marginal distribution over the third variable.WeightedPairDistribution.getFirstCount()
Gets the first marginal distribution.WeightedTripleDistribution.getJointCount()
The joint distribution over the three variables.WeightedPairDistribution.getJointCounts()
Gets the joint distribution.WeightedPairDistribution.getSecondCount()
Gets the second marginal distribution.Method parameters in org.tribuo.util.infotheory.impl with type arguments of type WeightCountTupleModifier and TypeMethodDescriptionstatic <T1,
T2> WeightedPairDistribution<T1, T2> WeightedPairDistribution.constructFromMap
(Map<CachedPair<T1, T2>, WeightCountTuple> jointCount) Generates a WeightedPairDistribution by generating the marginal distributions for the first and second elements.static <T1,
T2, T3> WeightedTripleDistribution<T1, T2, T3> WeightedTripleDistribution.constructFromMap
(Map<CachedTriple<T1, T2, T3>, WeightCountTuple> jointCount) Constructs a WeightedTripleDistribution by marginalising the supplied joint distribution.Constructor parameters in org.tribuo.util.infotheory.impl with type arguments of type WeightCountTupleModifierConstructorDescriptionWeightedPairDistribution
(long count, LinkedHashMap<CachedPair<T1, T2>, WeightCountTuple> jointCounts, LinkedHashMap<T1, WeightCountTuple> firstCount, LinkedHashMap<T2, WeightCountTuple> secondCount) Constructs a weighted pair distribution from the supplied values.WeightedPairDistribution
(long count, Map<CachedPair<T1, T2>, WeightCountTuple> jointCounts, Map<T1, WeightCountTuple> firstCount, Map<T2, WeightCountTuple> secondCount) Constructs a weighted pair distribution from the supplied values.WeightedTripleDistribution
(long count, Map<CachedTriple<T1, T2, T3>, WeightCountTuple> jointCount, Map<CachedPair<T1, T2>, WeightCountTuple> abCount, Map<CachedPair<T1, T3>, WeightCountTuple> acCount, Map<CachedPair<T2, T3>, WeightCountTuple> bcCount, Map<T1, WeightCountTuple> aCount, Map<T2, WeightCountTuple> bCount, Map<T3, WeightCountTuple> cCount) Constructs a weighted triple distribution from the supplied values.