HiddenMarkovClassifierTDistribution Class

Note: This API is now obsolete.

Obsolete. Please use HiddenMarkovClassifierTDistribution, TObservation instead.

Inheritance Hierarchy

SystemObject
Accord.Statistics.Models.MarkovBaseHiddenMarkovClassifierHiddenMarkovModelTDistribution
Accord.Statistics.Models.MarkovHiddenMarkovClassifierTDistribution

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

Syntax

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[SerializableAttribute]
[ObsoleteAttribute("Please use HiddenMarkovClassifier<TDistribution, TObservation> instead.")]
public class HiddenMarkovClassifier<TDistribution> : BaseHiddenMarkovClassifier<HiddenMarkovModel<TDistribution>>, 
	IEnumerable, IHiddenMarkovClassifier
where TDistribution : IDistribution

<SerializableAttribute>
<ObsoleteAttribute("Please use HiddenMarkovClassifier<TDistribution, TObservation> instead.")>
Public Class HiddenMarkovClassifier(Of TDistribution As IDistribution)
	Inherits BaseHiddenMarkovClassifier(Of HiddenMarkovModel(Of TDistribution))
	Implements IEnumerable, IHiddenMarkovClassifier

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Type Parameters

TDistribution

The HiddenMarkovClassifierTDistribution type exposes the following members.

Constructors

	Name	Description
	HiddenMarkovClassifierTDistribution(HiddenMarkovModelTDistribution)	Creates a new Sequence Classifier with the given number of classes.
	HiddenMarkovClassifierTDistribution(Int32, ITopology, TDistribution)	Creates a new Sequence Classifier with the given number of classes.
	HiddenMarkovClassifierTDistribution(Int32, ITopology, TDistribution)	Creates a new Sequence Classifier with the given number of classes.
	HiddenMarkovClassifierTDistribution(Int32, ITopology, TDistribution)	Creates a new Sequence Classifier with the given number of classes.
	HiddenMarkovClassifierTDistribution(Int32, ITopology, TDistribution)	Creates a new Sequence Classifier with the given number of classes.
	HiddenMarkovClassifierTDistribution(Int32, Int32, TDistribution)	Creates a new Sequence Classifier with the given number of classes.
	HiddenMarkovClassifierTDistribution(Int32, ITopology, TDistribution, String)	Creates a new Sequence Classifier with the given number of classes.
	HiddenMarkovClassifierTDistribution(Int32, ITopology, TDistribution, String)	Creates a new Sequence Classifier with the given number of classes.

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Properties

	Name	Description
	Classes	Gets the number of classes which can be recognized by this classifier. (Inherited from BaseHiddenMarkovClassifierTModel.)
	Dimension	Gets the number of dimensions of the observations handled by this classifier.
	Item	Gets the Hidden Markov Model implementation responsible for recognizing each of the classes given the desired class label. (Inherited from BaseHiddenMarkovClassifierTModel.)
	Models	Gets the collection of models specialized in each class of the sequence classification problem. (Inherited from BaseHiddenMarkovClassifierTModel.)
	Priors	Gets the prior distribution assumed for the classes. (Inherited from BaseHiddenMarkovClassifierTModel.)
	Sensitivity	Gets or sets a value governing the rejection given by a threshold model (if present). Increasing this value will result in higher rejection rates. Default is 1. (Inherited from BaseHiddenMarkovClassifierTModel.)
	Threshold	Gets or sets the threshold model. (Inherited from BaseHiddenMarkovClassifierTModel.)

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Methods

	Name	Description
	Compute(Array)	Computes the most likely class for a given sequence.
	Compute(Array, Double)	Computes the most likely class for a given sequence.
	Compute(Array, Double)	Computes the most likely class for a given sequence.
	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.)
	GetEnumerator	Returns an enumerator that iterates through the models in the classifier. (Inherited from BaseHiddenMarkovClassifierTModel.)
	GetHashCode	Serves as the default hash function. (Inherited from Object.)
	GetType	Gets the Type of the current instance. (Inherited from Object.)
	Load(Stream)	Obsolete. Loads a classifier from a stream.
	Load(String)	Obsolete. Loads a classifier from a file.
	LogLikelihood(Array)	Computes the log-likelihood that a sequence belongs any of the classes in the classifier.
	LogLikelihood(Array, Int32)	Computes the log-likelihood of a sequence belong to a given class according to this classifier.
	LogLikelihood(Array, Int32)	Computes the log-likelihood of a set of sequences belonging to their given respective classes according to this classifier.
	MemberwiseClone	Creates a shallow copy of the current Object. (Inherited from Object.)
	Save(Stream)	Obsolete. Saves the classifier to a stream.
	Save(String)	Obsolete. Saves the classifier to a stream.
	ToString	Returns a string that represents the current object. (Inherited from Object.)

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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.)
	SetEqualsHiddenMarkovModelTDistribution	Compares two enumerables for set equality. Two enumerables are set equal if they contain the same elements, but not necessarily in the same order. (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 Namespace

Accord.Statistics.Models.Markov.LearningHiddenMarkovClassifierLearningTDistribution, TObservation

Accord.Statistics.Models.MarkovHiddenMarkovClassifier

HiddenMarkovClassifierAddLanguageSpecificTextSet("LST4BF17078_0?cs=&lt;|vb=(Of |cpp=&lt;|fs=&lt;'|nu=(");TDistributionAddLanguageSpecificTextSet("LST4BF17078_1?cs=&gt;|vb=)|cpp=&gt;|fs=&gt;|nu=)"); Class

Type Parameters

Reference

HiddenMarkovClassifierTDistribution Class