Click or drag to resize

BayesServer.Analysis Namespace

Contains classes for performing analysis tasks that require inference and/or data, such as calculating value of information.
Classes
  ClassDescription
Public classAssociation
Calculates the strength between pairs of variables or sets of variables. Can be used to detect link strengths.
Public classAssociationOptions
Options that affect the link strength algorithm.
Public classAssociationOutput
Contains the results of an Association analysis.
Public classAssociationPair
Defines two sets of variables to be analyzed by the Association algorithm.
Public classAssociationPairOutput
Contains the results of the association calculations between two sets of variables.
Public classAutoInsight
Uses comparison queries to automatically derive insight about a target variable from a trained network.
Public classAutoInsightOptions
Options that affect auto-insight calculations.
Public classAutoInsightOutput
Contains the results obtained from AutoInsight.
Public classAutoInsightSamplingOptions
Options that affect any sampling required during auto-insight calculations.
Public classAutoInsightStateOutput
Contains the results obtained from AutoInsight for each test variable.
Public classAutoInsightStateOutputCollection
Represents a collection of AutoInsightStateOutput instances.
Public classAutoInsightVariableOutput
Represents the output obtained from AutoInsight for a test variable.
Public classAutoInsightVariableOutputCollection
Represents a collection of AutoInsightVariableOutput instances.
Public classClusterCount
Methods to determine the number of clusters (discrete states of a latent variable).
Public classClusterCountOptions
Options used by ClusterCount.
Public classClusterCountOutput
Output information returned from ClusterCount.
Public classClusterScore
Contains the results of a cluster configuration returned from ClusterCount.
Public classCombinationOptions
Determines which combinations are generated by Combinations.
Public classCombinations
Generates the available state combinations for a set of variables or counts.
Public classConfusionMatrix
Calculates a confusion matrix for a network which is used to predict discrete values (classification).
Public classConfusionMatrixCell
Contains statistics about a cell in a ConfusionMatrix.
Public classConstraintNotSatisfiedException
Exception raised when parameter tuning attempts to solve for a constraint that cannot be satisfied by the change(s) in parameters.
Public classConstraintSatisfiedException
Exception raised when parameter tuning attempts to solve for a constraint that is already true.
Public classCorrelation
Methods to convert covariance matrices to correlation matrices.
Public classHistogramDensity
Represents an empirical density function built from a histogram, which can represent arbitrary univariate distributions.
Public classHistogramDensityOptions
Options for learning a histogram based empirical density.
Public classImpact
Analyzes the impact of evidence.
Public classImpactHypothesisOutput
Output information about the hypothesis variable/state from an Impact analysis.
Public classImpactOptions
Options affecting how Impact analysis calculations are performed.
Public classImpactOutput
Contains the results of an Impact analysis.
Public classImpactOutputItem
The output from an impact analysis, for a particular subset of evidence.
Public classInSampleAnomalyDetection
Detects in-sample anomalies in a data set.
Public classInSampleAnomalyDetectionOptions
Options used by InSampleAnomalyDetection.
Public classInSampleAnomalyDetectionOutput
Output used by InSampleAnomalyDetection.
Public classLiftChart
Represents a lift chart, used to measure predictive performance.
Public classLiftChartPoint
Represents an XY coordinate in a lift chart.
Public classLogLikelihoodAnalysis
Analyzes the log-likelihood for different evidence subsets.
Public classLogLikelihoodAnalysisBaselineOutput
Output information about the log-likelihood from a log-likelihood analysis.
Public classLogLikelihoodAnalysisOptions
Options affecting how Log-Likelihood analysis calculations are performed.
Public classLogLikelihoodAnalysisOutput
Contains the results of a Log-Likelihood analysis.
Public classLogLikelihoodAnalysisOutputItem
The output from a Log-Likelihood analysis, for a particular subset of evidence.
Public classParameterReference
References a parameter in a node distribution.
Public classParameterTuning
Calculates how a parameter can be updated so that the resulting value of a hypothesis is within a given range.
Public classParameterTuningOneWay
Represents the result of one way parameter tuning.
Public classRegressionStatistics
Calculates statistics for a network which is used to predict continuous values (regression).
Public classSensitivityFunctionOneWay
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.
Public classSensitivityFunctionTwoWay
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.
Public classSensitivityToParameters
Calculates the affect of one or more parameters on the value of a hypothesis.
Public classValueOfInformation
Contains methods to determine what new evidence is most likely to reduce the uncertainty of a variable.
Public classValueOfInformationOptions
Options for calculating ValueOfInformation.
Public classValueOfInformationOutput
Contains the results of the tests carried out using ValueOfInformation.
Public classValueOfInformationTestOutput
Contains information about a variable tested via ValueOfInformation.
Interfaces
  InterfaceDescription
Public interfaceIEmpiricalDensity
Represents an empirical density function, which can represent arbitrary univariate distributions.
Enumerations
  EnumerationDescription
Public enumerationAutoInsightJSDivergence
Determines the type of Jensen Shannon divergence calculations, if any, performed during an auto insight analysis.
Public enumerationAutoInsightKLDivergence
Determines the type of KL divergence calculations, if any, performed during an auto insight analysis.
Public enumerationImpactSubsetMethod
Determines how subsets are determined during impact analysis.
Public enumerationLogLikelihoodAnalysisSubsetMethod
Determines how subsets are determined during a Log-Likelihood analysis.
Public enumerationValueOfInformationKind
The type of value of information statistic calculated.