Namespace BayesServer.Analysis
Classes
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 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.
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.
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.
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. The sensitivity function = P(h|e)(t) where h is the hypothesis state, e is the evidence, and t is the parameter being analyzed.
SensitivityFunctionTwoWay
Represents the result on a two-way sensitivity to parameters analysis. The sensitivity function = P(h|e)(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.
Interfaces
IEmpiricalDensity
Represents an empirical density function, which can represent arbitrary univariate distributions.
Enums
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.