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BaseViterbiLearningT Class
Base class for implementations of the Viterbi learning algorithm. This class cannot be instantiated.
Inheritance Hierarchy

Namespace:  Accord.Statistics.Models.Markov.Learning
Assembly:  Accord.Statistics (in Accord.Statistics.dll) Version: 3.8.0
Syntax
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public abstract class BaseViterbiLearning<T>
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Type Parameters

T

The BaseViterbiLearningT type exposes the following members.

Constructors
Properties
  NameDescription
Public propertyBatches
Gets or sets on how many batches the learning data should be divided during learning. Batches are used to estimate adequately the first models so they can better compute the Viterbi paths for subsequent passes of the algorithm. Default is 1.
Public propertyCurrentIteration
Gets the current iteration.
Public propertyHasConverged
Gets a value indicating whether this instance has converged.
Public propertyIterations Obsolete.
Please use MaxIterations instead.
Public propertyMaxIterations
Gets or sets the maximum number of iterations performed by the learning algorithm.
Public propertyToken
Gets or sets a cancellation token that can be used to stop the learning algorithm while it is running.
Public propertyTolerance
Gets or sets the maximum change in the average log-likelihood after an iteration of the algorithm used to detect convergence.
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Methods
  NameDescription
Protected methodComputeLogLikelihood
Computes the log-likelihood for the current model for the given observations.
Public methodEquals
Determines whether the specified object is equal to the current object.
(Inherited from Object.)
Protected methodFinalize
Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection.
(Inherited from Object.)
Public methodGetHashCode
Serves as the default hash function.
(Inherited from Object.)
Public methodGetType
Gets the Type of the current instance.
(Inherited from Object.)
Protected methodMemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
Public methodRun
Runs the learning algorithm.
Protected methodRunEpoch
Runs one single epoch (iteration) of the learning algorithm.
Public methodToString
Returns a string that represents the current object.
(Inherited from Object.)
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Extension Methods
  NameDescription
Public Extension MethodHasMethod
Checks whether an object implements a method with the given name.
(Defined by ExtensionMethods.)
Public Extension MethodIsEqual
Compares two objects for equality, performing an elementwise comparison if the elements are vectors or matrices.
(Defined by Matrix.)
Public Extension MethodTo(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.)
Public Extension MethodToTOverloaded.
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.)
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Remarks

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).

For the actual Viterbi classes, please refer to ViterbiLearning or ViterbiLearningTDistribution. For other kinds of algorithms, please see BaumWelchLearning and MaximumLikelihoodLearning and their generic counter-parts.

See Also