A compiled inference algorithm. The algorithm can be configured by setting observed values
and inference executed using Execute() or Initialise()/Update(). Following inference,
marginals can be extracted using Marginal().
Declaration Syntax| C# | Visual Basic | Visual C++ |
public class CompiledAlgorithm : IIterativeProcess
Public Class CompiledAlgorithm _ Implements IIterativeProcess
public ref class CompiledAlgorithm : IIterativeProcess
Members| All Members | Constructors | Methods | Properties | Fields | |
| Icon | Member | Description |
|---|---|---|
 | CompiledAlgorithm(IIterativeProcess, InferenceEngine) |
Creates a compiled algorithm object to wrap an instance of the
underlying compiled algorithm. This should only be called with
instances of classes generated by the Infer.NET compiler.
|
 | AlgorithmInstance |
The instance of the generated inference class which is being wrapped by
this CompiledAlgorithm.
|
| Engine |
The inference engine used to create this compiled algorithm.
|
| Execute()()() |
Executes the inference algorithm using the number of iterations specified in
the settings.
|
| Execute(Int32) |
Executes the inference algorithm for the specified number of iterations.
|
| GetObservedValue(String) |
Gets a specified observed value
|
| GetOutputMessage<(Of <(T>)>)(String) |
Get the output message for a given variable
|
| GetOutputMessage<(Of <(T>)>)(IVariable) |
Get the output message for a given variable
|
| Initialise()()() |
Initialises the messages
|
 | Iterations |
Iteration counter
|
| Marginal<(Of <(T>)>)(String) |
Returns the marginal distribution of the specified variable, cast to type T.
|
| Marginal<(Of <(T>)>)(String, String) |
Returns the path-specific marginal distribution of the specified variable, cast to type T.
|
| Marginal(String) |
Returns the marginal distribution of the specified variable.
|
| Marginal(String, String) |
Returns the path-specific marginal distribution of the specified variable.
For example, Gibbs sampling provides "Distribution", "Samples", and
"Distributions" paths
|
| Marginal(IVariable) |
Returns the marginal distribution of the specified variable.
|
| Marginal(IVariable, String) |
Returns the path-specific marginal distribution of the specified variable.
For example, Gibbs sampling provides "Distribution", "Samples", and
"Distributions" paths
|
| Marginal<(Of <(T>)>)(IVariable) |
Returns the marginal distribution of the specified variable, cast to type T.
|
| Marginal<(Of <(T>)>)(IVariable, String) |
Returns the marginal distribution of the specified variable, cast to type T.
|
| method |
The model method used for this algorithm, if known.
|
| ModelExpressions |
If the compiled algorithm was generated directly using the modelling API, this
stores the model expressions used to generate it.
|
| Reset()()() |
Resets the iteration counter back to zero.
|
| SetAllParameters(array<Object>[]()[]) |
Sets all observed variables in the order they were declared in the model.
|
| SetObservedValue(String, Object) |
Sets the specified observed value, and resets the model if the variable changed value
|
| SetObservedValue(String, Object, Boolean) |
Sets the specified observed value, and optionally resets the model if the variable changed value
|
| SetObservedValue(Variable) |
Sets the specified observed value on the model.
|
| SetObservedValue(Variable, Boolean) |
Sets the specified observed value.
|
| Update(Int32) |
Iterates the inference algorithm for a fixed number of iterations (with no initialisation).
|
| Update()()() |
Performs a single iteration of the inference algorithm
|
Inheritance Hierarchy| Object | |
 | CompiledAlgorithm |