HiddenMarkovClassifierLearningTDistribution Class

Note: This API is now obsolete.

Obsolete. Please use HiddenMarkovClassifierLearningTDistribution, TObservation instead.

Inheritance Hierarchy

SystemObject
Accord.Statistics.Models.Markov.LearningBaseHiddenMarkovClassifierLearningHiddenMarkovClassifierTDistribution, HiddenMarkovModelTDistribution
Accord.Statistics.Models.Markov.LearningHiddenMarkovClassifierLearningTDistribution

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

Syntax

Copy

[ObsoleteAttribute("Please use HiddenMarkovClassifierLearning<TDistribution, TObservation> instead.")]
public class HiddenMarkovClassifierLearning<TDistribution> : BaseHiddenMarkovClassifierLearning<HiddenMarkovClassifier<TDistribution>, HiddenMarkovModel<TDistribution>>
where TDistribution : IDistribution

<ObsoleteAttribute("Please use HiddenMarkovClassifierLearning<TDistribution, TObservation> instead.")>
Public Class HiddenMarkovClassifierLearning(Of TDistribution As IDistribution)
	Inherits BaseHiddenMarkovClassifierLearning(Of HiddenMarkovClassifier(Of TDistribution), HiddenMarkovModel(Of TDistribution))

Request Example View Source

Type Parameters

TDistribution

The HiddenMarkovClassifierLearningTDistribution type exposes the following members.

Constructors

	Name	Description
	HiddenMarkovClassifierLearningTDistribution	Creates a new instance of the learning algorithm for a given Markov sequence classifier using the specified configuration function.

Top

Properties

	Name	Description
	Algorithm	Gets or sets the configuration function specifying which training algorithm should be used for each of the models in the hidden Markov model set. (Inherited from BaseHiddenMarkovClassifierLearningTClassifier, TModel.)
	Classifier	Gets the classifier being trained by this instance. (Inherited from BaseHiddenMarkovClassifierLearningTClassifier, TModel.)
	Empirical	Gets or sets a value indicating whether the class priors should be estimated from the data, as in an empirical Bayes method. (Inherited from BaseHiddenMarkovClassifierLearningTClassifier, TModel.)
	Rejection	Gets or sets a value indicating whether a threshold model should be created or updated after training to support rejection. (Inherited from BaseHiddenMarkovClassifierLearningTClassifier, TModel.)

Top

Methods

	Name	Description
	ComputeError	Compute model error for a given data set.
	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. (Inherited from BaseHiddenMarkovClassifierLearningTClassifier, TModel.)
	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.)
	OnGenerativeClassModelLearningFinished	Raises the [E:GenerativeClassModelLearningFinished] event. (Inherited from BaseHiddenMarkovClassifierLearningTClassifier, TModel.)
	OnGenerativeClassModelLearningStarted	Raises the [E:GenerativeClassModelLearningStarted] event. (Inherited from BaseHiddenMarkovClassifierLearningTClassifier, TModel.)
	Run(Array, Int32)	Trains each model to recognize each of the output labels.
	RunT(T, Int32)	Obsolete. Trains each model to recognize each of the output labels. (Inherited from BaseHiddenMarkovClassifierLearningTClassifier, TModel.)
	Threshold	Creates a new threshold model for the current set of Markov models in this sequence classifier. (Overrides BaseHiddenMarkovClassifierLearningTClassifier, TModelThreshold.)
	ToString	Returns a string that represents the current object. (Inherited from Object.)

Top

Events

	Name	Description
	ClassModelLearningFinished	Occurs when the learning of a class model has finished. (Inherited from BaseHiddenMarkovClassifierLearningTClassifier, TModel.)
	ClassModelLearningStarted	Occurs when the learning of a class model has started. (Inherited from BaseHiddenMarkovClassifierLearningTClassifier, TModel.)

Top

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.)

Top

Reference

Accord.Statistics.Models.Markov.Learning Namespace

HiddenMarkovClassifierLearningAddLanguageSpecificTextSet("LST4504FA0F_0?cs=&lt;|vb=(Of |cpp=&lt;|fs=&lt;'|nu=(");TDistributionAddLanguageSpecificTextSet("LST4504FA0F_1?cs=&gt;|vb=)|cpp=&gt;|fs=&gt;|nu=)"); Class

Type Parameters

Reference

HiddenMarkovClassifierLearningTDistribution Class