Click or drag to resize
Accord.NET (logo)

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: 3.7.0
Syntax
public class HiddenConjugateGradientLearning<T> : BaseHiddenGradientOptimizationLearning<T, ConjugateGradient>, 
	ISupervisedLearning<HiddenConditionalRandomField<T>, T[], int>, IParallel, ISupportsCancellation, 
	IHiddenConditionalRandomFieldLearning<T>, IConvergenceLearning, IDisposable
Request Example View Source

Type Parameters

T

The HiddenConjugateGradientLearningT type exposes the following members.

Constructors
Properties
  NameDescription
Public propertyConverged Obsolete.
Please use HasConverged instead.
Public propertyCurrentIteration
Gets the current iteration number.
Public propertyFunction (Inherited from BaseHiddenConditionalRandomFieldLearningT.)
Public propertyHasConverged
Gets or sets whether the algorithm has converged.
(Inherited from BaseHiddenGradientOptimizationLearningTData, TOptimizer.)
Public propertyIterations Obsolete.
Please use MaxIterations instead.
Public propertyMaxIterations
Gets or sets the maximum number of iterations performed by the learning algorithm.
(Inherited from BaseHiddenGradientOptimizationLearningTData, TOptimizer.)
Public propertyModel
Gets or sets the model being trained.
(Inherited from BaseHiddenConditionalRandomFieldLearningT.)
Public propertyOptimizer
Gets the optimization algorithm being used.
(Inherited from BaseHiddenGradientOptimizationLearningTData, TOptimizer.)
Public propertyParallelOptions
Gets or sets the parallelization options for this algorithm.
(Inherited from BaseHiddenGradientOptimizationLearningTData, TOptimizer.)
Public propertyRegularization
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.)
Public propertyToken
Gets or sets a cancellation token that can be used to stop the learning algorithm while it is running.
(Inherited from BaseHiddenConditionalRandomFieldLearningT.)
Public propertyTolerance
Gets or sets the tolerance value used to determine whether the algorithm has converged.
(Inherited from BaseHiddenGradientOptimizationLearningTData, TOptimizer.)
Top
Methods
  NameDescription
Protected methodCreate
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.)
Protected methodCreateOptimizer
Inheritors of this class should create the optimization algorithm in this method, using the current MaxIterations and Tolerance settings.
(Overrides BaseHiddenGradientOptimizationLearningTData, TOptimizerCreateOptimizer.)
Public methodDispose
Performs application-defined tasks associated with freeing, releasing, or resetting unmanaged resources.
(Inherited from BaseHiddenGradientOptimizationLearningTData, TOptimizer.)
Protected methodDispose(Boolean)
Releases unmanaged and - optionally - managed resources
(Inherited from BaseHiddenGradientOptimizationLearningTData, TOptimizer.)
Public methodEquals
Determines whether the specified object is equal to the current object.
(Inherited from Object.)
Protected methodFinalize (Inherited from BaseHiddenGradientOptimizationLearningTData, TOptimizer.)
Public methodGetHashCode
Serves as the default hash function.
(Inherited from Object.)
Public methodGetType
Gets the Type of the current instance.
(Inherited from Object.)
Protected methodInnerRun
Runs the learning algorithm.
(Inherited from BaseHiddenGradientOptimizationLearningTData, TOptimizer.)
Public methodLearn
Learns a model that can map the given inputs to the given outputs.
(Inherited from BaseHiddenConditionalRandomFieldLearningT.)
Protected methodMemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
Public methodRun(TData, Int32)
Online learning is not supported.
(Inherited from BaseHiddenGradientOptimizationLearningTData, TOptimizer.)
Public methodRun(TData, Int32) Obsolete.
Runs the learning algorithm with the specified input training observations and corresponding output labels.
(Inherited from BaseHiddenGradientOptimizationLearningTData, TOptimizer.)
Public methodRunEpoch Obsolete.
Online learning is not supported.
(Inherited from BaseHiddenGradientOptimizationLearningTData, TOptimizer.)
Public methodToString
Returns a string that represents the current object.
(Inherited from Object.)
Top
Events
  NameDescription
Public eventProgressChanged
Occurs when the current learning progress has changed.
Top
Extension Methods
  NameDescription
Public Extension MethodHasMethod
Checks whether an object implements a method with the given name.
(Defined by ExtensionMethods.)
Public Extension MethodIsEqual
Compares two objects for equality, performing an elementwise comparison if the elements are vectors or matrices.
(Defined by Matrix.)
Public Extension MethodToT
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
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.

See Also