Uses of Class
com.bayesserver.Interval

Packages that use Interval

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

Uses of Interval in com.bayesserver.analysis

Methods in com.bayesserver.analysis that return Interval

Modifier and Type	Method	Description
Interval<Double>	AutoInsightOutput.getContinuousTargetInterval()	Gets the target interval (if any).
Interval<Double>	HistogramDensityItem.getInterval()	The histogram density interval.
Interval<Double>	ParameterTuningOneWay.getInterval()	Gets the interval for the parameter which satisfies the constraint used in parameter tuning.

Methods in com.bayesserver.analysis with parameters of type Interval

Modifier and Type	Method	Description
static ParameterTuningOneWay	ParameterTuning.oneWayDifference(SensitivityFunctionOneWay f1, SensitivityFunctionOneWay f2, Interval<Double> constraint)	Given a pair of sensitivity functions (evaluated on the same parameter and evidence but different hypotheses), determines how the parameter under consideration can be altered so that the difference between the hypothesis probabilities P(h1|e) - P(h2|e) is within a given range.
static ParameterTuningOneWay	ParameterTuning.oneWayRatio(SensitivityFunctionOneWay f1, SensitivityFunctionOneWay f2, Interval<Double> constraint)	Given a pair of sensitivity functions (evaluated on the same parameter and evidence but different hypotheses), determines how the parameter under consideration can be altered so that the ratio between the hypothesis probabilities P(h1|e) / P(h2|e) is within a given range.
static ParameterTuningOneWay	ParameterTuning.oneWaySimple(SensitivityFunctionOneWay f, Interval<Double> constraint)	Given a sensitivity function, determines how the parameter under consideration can be altered so that the resulting value of the hypothesis is within a given range.
void	AutoInsightOutput.setContinuousTargetInterval(Interval<Double> value)	Gets the target interval (if any).

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

Modifier and Type	Method	Description
static AutoInsightOutput[]	AutoInsight.calculate(Variable continuousTarget, List<Interval<Double>> targetIntervals, List<Variable> testVariables, Evidence evidence, AutoInsightOptions options)	Uses comparison queries to automatically derive insight about a target variable from a trained network.

Constructor parameters in com.bayesserver.analysis with type arguments of type Interval

Constructor	Description
HistogramDensity(List<Interval<Double>> intervals, List<Double> intervalCounts)	Constructs an empirical density function.

Uses of Interval in com.bayesserver.data.discovery

Methods in com.bayesserver.data.discovery that return types with arguments of type Interval

Modifier and Type	Method	Description
List<Interval<Double>>	Clustering.discretize(Iterable<Double> unsortedData, DiscretizationOptions options, String dataColumn)	Discretizes unsorted continuous data that may contain missing (null) values.
List<Interval<Double>>	Discretize.discretize(Iterable<Double> unsortedData, DiscretizationOptions options, String dataColumn)	Discretizes unsorted continuous data that may contain missing (null) values.
List<Interval<Double>>	EqualFrequencies.discretize(Iterable<Double> unsortedData, DiscretizationOptions options, String dataColumn)	Discretizes unsorted continuous data that may contain missing (null) values.
List<Interval<Double>>	EqualIntervals.discretize(Iterable<Double> unsortedData, DiscretizationOptions options, String dataColumn)	Discretizes unsorted continuous data that may contain missing (null) values.
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.
List<Interval<Double>>	DiscretizationInfo.getIntervals()	Gets the intervals generated by a discretization algorithm for a column of data.