BaseBaumWelchLearning Class 
Note: This API is now obsolete.
Namespace: Accord.Statistics.Models.Markov.Learning
[ObsoleteAttribute("This class will be removed")] public abstract class BaseBaumWelchLearning : IConvergenceLearning
The BaseBaumWelchLearning type exposes the following members.
Name  Description  

BaseBaumWelchLearning 
Initializes a new instance of the BaseBaumWelchLearning class.

Name  Description  

CurrentIteration 
Gets or sets the number of performed iterations.
 
HasConverged 
Gets or sets whether the algorithm has converged.
 
Iterations  Obsolete.
Please use MaxIterations instead.
 
LogGamma 
Gets the Gamma matrix of log probabilities created during
the last iteration of the BaumWelch learning algorithm.
 
LogKsi 
Gets the Ksi matrix of log probabilities created during
the last iteration of the BaumWelch learning algorithm.
 
LogWeights 
Gets the sample weights in the last iteration of the
BaumWelch learning algorithm.
 
MaxIterations 
Gets or sets the maximum number of iterations
performed by the learning algorithm.
 
Tolerance 
Gets or sets the maximum change in the average loglikelihood
after an iteration of the algorithm used to detect convergence.

Name  Description  

ComputeForwardBackward 
Computes the forward and backward probabilities matrices
for a given observation referenced by its index in the
input training data.
 
ComputeKsi 
Computes the ksi matrix of probabilities for a given observation
referenced by its index in the input training data.
 
Equals  Determines whether the specified object is equal to the current object. (Inherited from Object.)  
Finalize  Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object.)  
GetHashCode  Serves as the default hash function. (Inherited from Object.)  
GetType  Gets the Type of the current instance. (Inherited from Object.)  
MemberwiseClone  Creates a shallow copy of the current Object. (Inherited from Object.)  
Run(Array) 
Runs the BaumWelch learning algorithm for hidden Markov models.
 
Run(Array, Double) 
Runs the BaumWelch learning algorithm for hidden Markov models.
 
ToString  Returns a string that represents the current object. (Inherited from Object.)  
UpdateEmissions 
Updates the emission probability matrix.

Name  Description  

HasMethod 
Checks whether an object implements a method with the given name.
(Defined by ExtensionMethods.)  
IsEqual 
Compares two objects for equality, performing an elementwise
comparison if the elements are vectors or matrices.
(Defined by Matrix.)  
To(Type)  Overloaded.
Converts an object into another type, irrespective of whether
the conversion can be done at compile time or not. This can be
used to convert generic types to numeric types during runtime.
(Defined by ExtensionMethods.)  
ToT  Overloaded.
Converts an object into another type, irrespective of whether
the conversion can be done at compile time or not. This can be
used to convert generic types to numeric types during runtime.
(Defined by ExtensionMethods.) 
This class uses a template method pattern so specialized classes can be written for each kind of hidden Markov model emission density (either discrete or continuous). The methods UpdateEmissions, ComputeForwardBackward(Int32, Double, Double) and ComputeKsi(Int32, Double, Double) should be overridden by inheriting classes to specify how those probabilities should be computed for the density being modeled.
For the actual BaumWelch classes, please refer to BaumWelchLearning or BaumWelchLearningTDistribution. For other kinds of algorithms, please see ViterbiLearning and MaximumLikelihoodLearning and their generic counterparts.