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Accord.NET (logo) BaseHiddenMarkovClassifierLearningTClassifier, TModel, TDistribution, TObservation Class
Abstract base class for Sequence Classifier 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: 3.4.0
Syntax
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>
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Type Parameters

TClassifier
TModel
TDistribution
TObservation

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

Constructors
  NameDescription
Protected methodBaseHiddenMarkovClassifierLearningTClassifier, TModel, TDistribution, TObservation(TClassifier)
Creates a new instance of the learning algorithm for a given Markov sequence classifier using the specified configuration function.
Protected methodBaseHiddenMarkovClassifierLearningTClassifier, 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.
Protected methodBaseHiddenMarkovClassifierLearningTClassifier, 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
  NameDescription
Public propertyAlgorithm Obsolete.
Obsolete.
Public propertyClassifier
Gets the classifier being trained by this instance.
Public propertyEmpirical
Gets or sets a value indicating whether the class priors should be estimated from the data, as in an empirical Bayes method.
Public propertyLearner
Gets or sets the configuration function specifying which training algorithm should be used for each of the models in the hidden Markov model set.
Public propertyLogLikelihood
Gets the log-likelihood at the end of the training.
Public propertyParallelOptions
Gets or sets the parallelization options for this algorithm.
Public propertyRejection
Gets or sets a value indicating whether a threshold model should be created or updated after training to support rejection.
Public propertyToken
Gets or sets a cancellation token that can be used to stop the learning algorithm while it is running.
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Methods
  NameDescription
Protected methodCreateThresholdTopology
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.
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.)
Protected methodOnGenerativeClassModelLearningFinished
Raises the [E:GenerativeClassModelLearningFinished] event.
Protected methodOnGenerativeClassModelLearningStarted
Raises the [E:GenerativeClassModelLearningStarted] event.
Protected methodRunT Obsolete.
Trains each model to recognize each of the output labels.
Public methodThreshold
Creates a new threshold model for the current set of Markov models in this sequence classifier.
Public methodToString
Returns a string that represents the current object.
(Inherited from Object.)
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Events
  NameDescription
Public eventClassModelLearningFinished
Occurs when the learning of a class model has finished.
Public eventClassModelLearningStarted
Occurs when the learning of a class model has started.
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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 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.)
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 Matrix.)
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See Also