BaseHiddenMarkovClassifierLearningTClassifier, TModel, TDistribution, TObservation Class

Abstract base class for hidden Markov model learning algorithms.

Inheritance Hierarchy

SystemObject
  Accord.Statistics.Models.Markov.LearningBaseHiddenMarkovClassifierLearningTClassifier, TModel, TDistribution, TObservation
    Accord.Statistics.Models.Markov.LearningHiddenMarkovClassifierLearning
    Accord.Statistics.Models.Markov.LearningHiddenMarkovClassifierLearningTDistribution, TObservation

Namespace: Accord.Statistics.Models.Markov.Learning
Assembly: Accord.Statistics (in Accord.Statistics.dll) Version: 3.8.0

Syntax

Copy

public abstract class BaseHiddenMarkovClassifierLearning<TClassifier, TModel, TDistribution, TObservation> : ISupervisedLearning<TClassifier, TObservation[], int>, 
	IParallel, ISupportsCancellation
where TClassifier : BaseHiddenMarkovClassifier<TModel, TDistribution, TObservation>
where TModel : HiddenMarkovModel<TDistribution, TObservation>
where TDistribution : Object, IDistribution<TObservation>

Public MustInherit Class BaseHiddenMarkovClassifierLearning(Of TClassifier As BaseHiddenMarkovClassifier(Of TModel, TDistribution, TObservation), TModel As HiddenMarkovModel(Of TDistribution, TObservation), TDistribution As {Object, IDistribution(Of TObservation)}, TObservation)
	Implements ISupervisedLearning(Of TClassifier, TObservation(), Integer), 
	IParallel, ISupportsCancellation

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Type Parameters

TClassifier
TModel
TDistribution
TObservation

The BaseHiddenMarkovClassifierLearningTClassifier, TModel, TDistribution, TObservation type exposes the following members.

Constructors

	Name	Description
	BaseHiddenMarkovClassifierLearningTClassifier, TModel, TDistribution, TObservation	Creates a new instance of the learning algorithm for a given Markov sequence classifier using the specified configuration function.
	BaseHiddenMarkovClassifierLearningTClassifier, TModel, TDistribution, TObservation(TClassifier)	Creates a new instance of the learning algorithm for a given Markov sequence classifier using the specified configuration function.
	BaseHiddenMarkovClassifierLearningTClassifier, TModel, TDistribution, TObservation(TClassifier, ClassifierLearningAlgorithmConfiguration)	Obsolete. Creates a new instance of the learning algorithm for a given Markov sequence classifier using the specified configuration function.
	BaseHiddenMarkovClassifierLearningTClassifier, TModel, TDistribution, TObservation(TClassifier, FuncInt32, IUnsupervisedLearningTModel, TObservation, Int32)	Creates a new instance of the learning algorithm for a given Markov sequence classifier using the specified configuration function.

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Properties

	Name	Description
	Algorithm	Obsolete. Obsolete.
	Classifier	Gets the classifier being trained by this instance.
	Empirical	Gets or sets a value indicating whether the class priors should be estimated from the data, as in an empirical Bayes method.
	Learner	Gets or sets the configuration function specifying which training algorithm should be used for each of the models in the hidden Markov model set.
	LogLikelihood	Gets the log-likelihood at the end of the training.
	ParallelOptions	Gets or sets the parallelization options for this algorithm.
	Rejection	Gets or sets a value indicating whether a threshold model should be created or updated after training to support rejection.
	Token	Gets or sets a cancellation token that can be used to stop the learning algorithm while it is running.

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Methods

	Name	Description
	Create	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.
	CreateThresholdTopology	Creates the state transition topology for the threshold model. This method can be used to help in the implementation of the Threshold abstract method which has to be defined for implementers of this class.
	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.)
	Learn	Learns a model that can map the given inputs to the given outputs.
	MemberwiseClone	Creates a shallow copy of the current Object. (Inherited from Object.)
	OnGenerativeClassModelLearningFinished	Raises the [E:GenerativeClassModelLearningFinished] event.
	OnGenerativeClassModelLearningStarted	Raises the [E:GenerativeClassModelLearningStarted] event.
	RunT	Obsolete. Trains each model to recognize each of the output labels.
	Threshold	Creates a new threshold model for the current set of Markov models in this sequence classifier.
	ToString	Returns a string that represents the current object. (Inherited from Object.)

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Events

	Name	Description
	ClassModelLearningFinished	Occurs when the learning of a class model has finished.
	ClassModelLearningStarted	Occurs when the learning of a class model has started.

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Extension Methods

	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.)

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Reference

Accord.Statistics.Models.Markov.Learning Namespace

BaseHiddenMarkovClassifierLearningAddLanguageSpecificTextSet("LSTD2C8C091_0?cs=&lt;|vb=(Of |cpp=&lt;|fs=&lt;'|nu=(");TClassifier, TModel, TDistribution, TObservationAddLanguageSpecificTextSet("LSTD2C8C091_1?cs=&gt;|vb=)|cpp=&gt;|fs=&gt;|nu=)"); Class

Type Parameters

Reference

BaseHiddenMarkovClassifierLearningTClassifier, TModel, TDistribution, TObservation Class