HiddenConjugateGradientLearningT Class

Conjugate Gradient learning algorithm for Hidden Conditional Hidden Fields.

Inheritance Hierarchy

SystemObject
  Accord.Statistics.Models.Fields.LearningBaseHiddenConditionalRandomFieldLearningT
    Accord.Statistics.Models.Fields.LearningBaseHiddenGradientOptimizationLearningT, ConjugateGradient
      Accord.Statistics.Models.Fields.LearningHiddenConjugateGradientLearningT

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

Syntax

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public class HiddenConjugateGradientLearning<T> : BaseHiddenGradientOptimizationLearning<T, ConjugateGradient>, 
	ISupervisedLearning<HiddenConditionalRandomField<T>, T[], int>, IParallel, ISupportsCancellation, 
	IHiddenConditionalRandomFieldLearning<T>, IConvergenceLearning, IDisposable

Public Class HiddenConjugateGradientLearning(Of T)
	Inherits BaseHiddenGradientOptimizationLearning(Of T, ConjugateGradient)
	Implements ISupervisedLearning(Of HiddenConditionalRandomField(Of T), T(), Integer), 
	IParallel, ISupportsCancellation, IHiddenConditionalRandomFieldLearning(Of T), IConvergenceLearning, IDisposable

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Type Parameters

T

The HiddenConjugateGradientLearningT type exposes the following members.

Constructors

	Name	Description
	HiddenConjugateGradientLearningT	Constructs a new Conjugate Gradient learning algorithm.

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Properties

	Name	Description
	Converged	Obsolete. Please use HasConverged instead.
	CurrentIteration	Gets the current iteration number.
	Function	Gets or sets the potential function to be used if this learning algorithm needs to create a new HiddenConditionalRandomFieldT. (Inherited from BaseHiddenConditionalRandomFieldLearningT.)
	HasConverged	Gets or sets whether the algorithm has converged. (Inherited from BaseHiddenGradientOptimizationLearningTData, TOptimizer.)
	Iterations	Obsolete. Please use MaxIterations instead.
	MaxIterations	Gets or sets the maximum number of iterations performed by the learning algorithm. (Inherited from BaseHiddenGradientOptimizationLearningTData, TOptimizer.)
	Model	Gets or sets the model being trained. (Inherited from BaseHiddenConditionalRandomFieldLearningT.)
	Optimizer	Gets the optimization algorithm being used. (Inherited from BaseHiddenGradientOptimizationLearningTData, TOptimizer.)
	ParallelOptions	Gets or sets the parallelization options for this algorithm. (Inherited from BaseHiddenGradientOptimizationLearningTData, TOptimizer.)
	Regularization	Gets or sets the amount of the parameter weights which should be included in the objective function. Default is 0 (do not include regularization). (Inherited from BaseHiddenGradientOptimizationLearningTData, TOptimizer.)
	Token	Gets or sets a cancellation token that can be used to stop the learning algorithm while it is running. (Inherited from BaseHiddenConditionalRandomFieldLearningT.)
	Tolerance	Gets or sets the tolerance value used to determine whether the algorithm has converged. (Inherited from BaseHiddenGradientOptimizationLearningTData, TOptimizer.)

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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. (Inherited from BaseHiddenConditionalRandomFieldLearningT.)
	CreateOptimizer	Inheritors of this class should create the optimization algorithm in this method, using the current MaxIterations and Tolerance settings. (Overrides BaseHiddenGradientOptimizationLearningTData, TOptimizerCreateOptimizer.)
	Dispose	Performs application-defined tasks associated with freeing, releasing, or resetting unmanaged resources. (Inherited from BaseHiddenGradientOptimizationLearningTData, TOptimizer.)
	Dispose(Boolean)	Releases unmanaged and - optionally - managed resources (Inherited from BaseHiddenGradientOptimizationLearningTData, TOptimizer.)
	Equals	Determines whether the specified object is equal to the current object. (Inherited from Object.)
	Finalize	Releases unmanaged resources and performs other cleanup operations before the HiddenQuasiNewtonLearningT is reclaimed by garbage collection. (Inherited from BaseHiddenGradientOptimizationLearningTData, TOptimizer.)
	GetHashCode	Serves as the default hash function. (Inherited from Object.)
	GetType	Gets the Type of the current instance. (Inherited from Object.)
	InnerRun	Runs the learning algorithm. (Inherited from BaseHiddenGradientOptimizationLearningTData, TOptimizer.)
	Learn	Learns a model that can map the given inputs to the given outputs. (Inherited from BaseHiddenConditionalRandomFieldLearningT.)
	MemberwiseClone	Creates a shallow copy of the current Object. (Inherited from Object.)
	Run(TData, Int32)	Online learning is not supported. (Inherited from BaseHiddenGradientOptimizationLearningTData, TOptimizer.)
	Run(TData, Int32)	Obsolete. Runs the learning algorithm with the specified input training observations and corresponding output labels. (Inherited from BaseHiddenGradientOptimizationLearningTData, TOptimizer.)
	RunEpoch	Obsolete. Online learning is not supported. (Inherited from BaseHiddenGradientOptimizationLearningTData, TOptimizer.)
	ToString	Returns a string that represents the current object. (Inherited from Object.)

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Events

	Name	Description
	ProgressChanged	Occurs when the current learning progress has changed.

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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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Examples

For an example on how to learn Hidden Conditional Random Fields, please see the Hidden Resilient Gradient Learning page. All learning algorithms can be utilized in a similar manner.

Reference

Accord.Statistics.Models.Fields.Learning Namespace

HiddenConjugateGradientLearningAddLanguageSpecificTextSet("LSTCE2AB2CF_0?cs=&lt;|vb=(Of |cpp=&lt;|fs=&lt;'|nu=(");TAddLanguageSpecificTextSet("LSTCE2AB2CF_1?cs=&gt;|vb=)|cpp=&gt;|fs=&gt;|nu=)"); Class

Type Parameters

Reference

HiddenConjugateGradientLearningT Class