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BaseMaximumLikelihoodLearningTModel, TDistribution, TObservation, TOptions Class

Base class for observable Markov model learning algorithms.
Inheritance Hierarchy
SystemObject
  Accord.Statistics.Models.Markov.LearningBaseMaximumLikelihoodLearningTModel, TDistribution, TObservation, TOptions
    Accord.Statistics.Models.Markov.LearningMaximumLikelihoodLearning
    Accord.Statistics.Models.Markov.LearningMaximumLikelihoodLearningTDistribution, TObservation

Namespace:  Accord.Statistics.Models.Markov.Learning
Assembly:  Accord.Statistics (in Accord.Statistics.dll) Version: 3.8.0
Syntax
public abstract class BaseMaximumLikelihoodLearning<TModel, TDistribution, TObservation, TOptions>
where TModel : HiddenMarkovModel<TDistribution, TObservation>
where TDistribution : Object, IFittableDistribution<TObservation>
where TOptions : IFittingOptions
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Type Parameters

TModel
TDistribution
TObservation
TOptions

The BaseMaximumLikelihoodLearningTModel, TDistribution, TObservation, TOptions type exposes the following members.

Constructors
Properties
  NameDescription
Public propertyEmissions
Gets or sets the function that initializes the emission distributions in the hidden Markov Models.
Public propertyFittingOptions
Gets or sets the distribution fitting options to use when estimating distribution densities during learning.
Public propertyModel
Gets the model being trained.
Public propertyToken
Gets or sets a cancellation token that can be used to stop the learning algorithm while it is running.
Public propertyUseLaplaceRule
Gets or sets whether to use Laplace's rule of succession to avoid zero probabilities.
Public propertyUseWeights
Gets or sets whether the emission fitting algorithm should present weighted samples or simply the clustered samples to the density estimation methods.
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Methods
  NameDescription
Protected methodCreate
Creates an instance of the model to be learned. Inheritors of this abstract class must define this method so new models can be created from the training data.
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.)
Public methodLearn
Learns a model that can map the given inputs to the given outputs.
Protected methodMemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
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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See Also