Uses of Class
com.bayesserver.data.discovery.WeightedValue

Packages that use WeightedValue

Package	Description
com.bayesserver.analysis
com.bayesserver.data.discovery

Uses of WeightedValue in com.bayesserver.analysis

Method parameters in com.bayesserver.analysis with type arguments of type WeightedValue

Modifier and Type	Method	Description
static HistogramDensity	HistogramDensity.learn(Iterable<WeightedValue> values, HistogramDensityOptions options)	Learns a univariate empirical density from data.

Uses of WeightedValue in com.bayesserver.data.discovery

Method parameters in com.bayesserver.data.discovery with type arguments of type WeightedValue

Modifier and Type	Method	Description
List<Interval<Double>>	Clustering.discretizeWeighted(Iterable<WeightedValue> unsortedData, DiscretizationOptions options, String dataColumn)	Discretizes unsorted weighted continuous data that may contain missing (null) values.
List<Interval<Double>>	Discretize.discretizeWeighted(Iterable<WeightedValue> unsortedData, DiscretizationOptions options, String dataColumn)	Discretizes unsorted weighted continuous data that may contain missing (null) values.
List<Interval<Double>>	EqualFrequencies.discretizeWeighted(Iterable<WeightedValue> unsortedData, DiscretizationOptions options, String dataColumn)	Discretizes unsorted weighted continuous data that may contain missing (null) values.
List<Interval<Double>>	EqualIntervals.discretizeWeighted(Iterable<WeightedValue> unsortedData, DiscretizationOptions options, String dataColumn)	Discretizes unsorted weighted continuous data that may contain missing (null) values.