Package com.bayesserver.analysis

Interface Summary

Interface	Description
ClusterCountActions	Actions which the caller must implement to use 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.
EmpiricalDensity	Represents an empirical density function, which can represent arbitrary univariate distributions.
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.
InSampleAnomalyDetectionActions	Actions which the caller must implement to use InSampleAnomalyDetection.
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.

Class Summary

Class	Description
Association	Calculates the strength between pairs of variables or sets of variables.
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.
AutoInsight	Uses comparison queries to automatically derive insight about a target variable from a trained network.
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.
ClusterCount	Methods to determine the number of clusters (discrete states of a latent variable).
ClusterCountOptions	Options used by ClusterCount.
ClusterCountOutput	Output information returned from ClusterCount.
ClusterScore	Contains the results of a cluster configuration returned from ClusterCount.
CombinationOptions	Determines which combinations are generated by Combinations.
Combinations	Generates the available state combinations for a set of variables or counts.
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.
Correlation	Methods to convert covariance matrices to correlation matrices.
DSeparation	Contains methods to calculate D-Separation.
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.
HistogramDensity	Represents an empirical density function built from a histogram, which can represent arbitrary univariate distributions.
HistogramDensityItem	Information about each interval in the histogram density.
HistogramDensityOptions	Options for learning a histogram based empirical density.
Impact	Analyzes the impact of evidence.
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.
InSampleAnomalyDetection	Detects in-sample anomalies in a data set.
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.
LogLikelihoodAnalysis	Analyzes the log-likelihood for different evidence subsets.
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.
ParameterReference	References a parameter in a node distribution.
ParameterTuning	Calculates how a parameter can be updated so that the resulting value of a hypothesis is within a given range.
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.
SensitivityToParameters	Calculates the affect of one or more parameters on the value of a hypothesis.
ValueOfInformation	Contains methods to determine what new evidence is most likely to reduce the uncertainty of a variable.
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.

Enum Summary

Enum	Description
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.
DSeparationCategory	The result of a D-Separation test.
ImpactSubsetMethod	Determines how subsets are determined during impact analysis.
LogLikelihoodAnalysisSubsetMethod	Determines how subsets are determined during a Log-Likelihood analysis.
ValueOfInformationKind	The type of value of information statistic calculated.

Exception Summary

Exception	Description
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.