Uses of Package
com.bayesserver.analysis

Packages that use com.bayesserver.analysis

Package	Description
com.bayesserver.analysis

Classes in com.bayesserver.analysis used by com.bayesserver.analysis

Class and Description
AssociationOptions Options that affect the link strength algorithm.
AssociationOutput Contains the results of an Association analysis.
AssociationPair Defines two sets of variables to be analyzed by the Association algorithm.
AssociationPairOutput Contains the results of the association calculations between two sets of variables.
AutoInsightJSDivergence Determines the type of Jensen Shannon divergence calculations, if any, performed during an auto insight analysis.
AutoInsightKLDivergence Determines the type of KL divergence calculations, if any, performed during an auto insight analysis.
AutoInsightOptions Options that affect auto-insight calculations.
AutoInsightOutput Contains the results obtained from AutoInsight.
AutoInsightSamplingOptions Options that affect any sampling required during auto-insight calculations.
AutoInsightStateOutput Contains the results obtained from AutoInsight for each test variable.
AutoInsightStateOutputCollection Represents a collection of AutoInsightStateOutput instances.
AutoInsightVariableOutput Represents the output obtained from AutoInsight for a test variable.
AutoInsightVariableOutputCollection Represents a collection of AutoInsightVariableOutput instances.
ClusterCountActions Actions which the caller must implement to use ClusterCount.
ClusterCountOptions Options used by ClusterCount.
ClusterCountOutput Output information returned from ClusterCount.
ClusterScore Contains the results of a cluster configuration returned from ClusterCount.
CombinationAction Interface to receive combinations from the Combinations.enumerate(java.util.List<com.bayesserver.Variable>, com.bayesserver.analysis.CombinationAction, com.bayesserver.analysis.CombinationOptions) method.
CombinationOptions Determines which combinations are generated by Combinations.
ConfusionMatrix Calculates a confusion matrix for a network which is used to predict discrete values (classification).
ConfusionMatrixCell Contains statistics about a cell in a ConfusionMatrix.
ConstraintNotSatisfiedException Exception raised when parameter tuning attempts to solve for a constraint that cannot be satisfied by the change(s) in parameters.
ConstraintSatisfiedException Exception raised when parameter tuning attempts to solve for a constraint that is already true.
DSeparationCategory The result of a D-Separation test.
DSeparationOptions Options for calculating D-Separation.
DSeparationOutput Contains the results of a test for D-Separation.
DSeparationTestResult The result of a D-Separation check for a test node.
DSeparationTestResultCollection Collection of D-Separation test results.
EmpiricalDensity Represents an empirical density function, which can represent arbitrary univariate distributions.
HistogramDensity Represents an empirical density function built from a histogram, which can represent arbitrary univariate distributions.
HistogramDensityOptions Options for learning a histogram based empirical density.
ImpactAction Interface to receive impact outputs from the Impact.calculate(com.bayesserver.Network, com.bayesserver.Variable, com.bayesserver.State, com.bayesserver.inference.Evidence, java.util.List<com.bayesserver.Variable>, com.bayesserver.analysis.ImpactOptions) method.
ImpactHypothesisOutput Output information about the hypothesis variable/state from an Impact analysis.
ImpactOptions Options affecting how Impact analysis calculations are performed.
ImpactOutput Contains the results of an Impact analysis.
ImpactOutputItem The output from an impact analysis, for a particular subset of evidence.
ImpactSubsetMethod Determines how subsets are determined during impact analysis.
InSampleAnomalyDetection Detects in-sample anomalies in a data set.
InSampleAnomalyDetectionActions Actions which the caller must implement to use InSampleAnomalyDetection.
InSampleAnomalyDetectionOptions Options used by InSampleAnomalyDetection.
InSampleAnomalyDetectionOutput Output used by InSampleAnomalyDetection.
LiftChart Represents a lift chart, used to measure predictive performance.
LiftChartPoint Represents an XY coordinate in a lift chart.
LogLikelihoodAnalysisAction Interface to receive Log-Likelihood analysis outputs from the LogLikelihoodAnalysis.calculate(com.bayesserver.Network, com.bayesserver.inference.Evidence, java.util.List<com.bayesserver.Variable>, com.bayesserver.analysis.LogLikelihoodAnalysisOptions) method.
LogLikelihoodAnalysisBaselineOutput Output information about the log-likelihood from a log-likelihood analysis.
LogLikelihoodAnalysisOptions Options affecting how Log-Likelihood analysis calculations are performed.
LogLikelihoodAnalysisOutput Contains the results of a Log-Likelihood analysis.
LogLikelihoodAnalysisOutputItem The output from a Log-Likelihood analysis, for a particular subset of evidence.
LogLikelihoodAnalysisSubsetMethod Determines how subsets are determined during a Log-Likelihood analysis.
ParameterReference References a parameter in a node distribution.
ParameterTuningOneWay Represents the result of one way parameter tuning.
RegressionStatistics Calculates statistics for a network which is used to predict continuous values (regression).
SensitivityFunctionOneWay Represents the result on a one-way sensitivity to parameters analysis.
SensitivityFunctionTwoWay Represents the result on a two-way sensitivity to parameters analysis.
ValueOfInformationKind The type of value of information statistic calculated.
ValueOfInformationOptions Options for calculating ValueOfInformation.
ValueOfInformationOutput Contains the results of the tests carried out using ValueOfInformation.
ValueOfInformationTestOutput Contains information about a variable tested via ValueOfInformation.