BayesServer.Analysis Namespace 
Class  Description  

Association 
Calculates the strength between pairs of variables or sets of variables. Can be used to detect link strengths.
 
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 autoinsight calculations.
 
AutoInsightOutput 
Contains the results obtained from AutoInsight.
 
AutoInsightSamplingOptions 
Options that affect any sampling required during autoinsight 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.
 
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.
 
Correlation 
Methods to convert covariance matrices to correlation matrices.
 
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.
 
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 insample 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 loglikelihood for different evidence subsets.
 
LogLikelihoodAnalysisBaselineOutput 
Output information about the loglikelihood from a loglikelihood analysis.
 
LogLikelihoodAnalysisOptions 
Options affecting how LogLikelihood analysis calculations are performed.
 
LogLikelihoodAnalysisOutput 
Contains the results of a LogLikelihood analysis.
 
LogLikelihoodAnalysisOutputItem 
The output from a LogLikelihood 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 oneway sensitivity to parameters analysis. The sensitivity function = P(he)(t) where h is the hypothesis state, e is the evidence, and t is the parameter being analyzed.
 
SensitivityFunctionTwoWay 
Represents the result on a twoway sensitivity to parameters analysis. The sensitivity function = P(he)(t1, t2) where h is the hypothesis state, e is the evidence, and t1 and t2 are the the parameters being analyzed.
 
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.

Interface  Description  

IEmpiricalDensity 
Represents an empirical density function, which can represent arbitrary univariate distributions.

Enumeration  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.
 
ImpactSubsetMethod 
Determines how subsets are determined during impact analysis.
 
LogLikelihoodAnalysisSubsetMethod 
Determines how subsets are determined during a LogLikelihood analysis.
 
ValueOfInformationKind 
The type of value of information statistic calculated.
