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BaseHiddenMarkovModelLearningTModel, TObservation Class |
Base class for implementations of the Baum-Welch learning algorithm.
This class cannot be instantiated.
Inheritance HierarchySystemObject
Accord.MachineLearningParallelLearningBase
Accord.Statistics.Models.Markov.LearningBaseHiddenMarkovModelLearningTModel, TObservation
Accord.Statistics.Models.Markov.LearningBaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions
Accord.MachineLearningParallelLearningBase
Accord.Statistics.Models.Markov.LearningBaseHiddenMarkovModelLearningTModel, TObservation
Accord.Statistics.Models.Markov.LearningBaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions
Namespace: Accord.Statistics.Models.Markov.Learning
Assembly: Accord.Statistics (in Accord.Statistics.dll) Version: 3.8.0
Syntaxpublic abstract class BaseHiddenMarkovModelLearning<TModel, TObservation> : ParallelLearningBase
Type Parameters
- TModel
- TObservation
The BaseHiddenMarkovModelLearningTModel, TObservation type exposes the following members.
Constructors| Name | Description | |
|---|---|---|
 | BaseHiddenMarkovModelLearningTModel, TObservation |
Initializes a new instance of the BaseHiddenMarkovModelLearningTModel, TObservation class.
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| BaseHiddenMarkovModelLearningTModel, TObservation(TModel) |
Initializes a new instance of the BaseHiddenMarkovModelLearningTModel, TObservation class.
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Properties| Name | Description | |
|---|---|---|
 | Model |
Gets or sets the model being trained.
|
| NumberOfStates |
Gets or sets the number of states to be used when this
learning algorithm needs to create new models.
|
| ParallelOptions |
Gets or sets the parallelization options for this algorithm.
(Inherited from ParallelLearningBase.) |
| Token |
Gets or sets a cancellation token that can be used
to cancel the algorithm while it is running.
(Inherited from ParallelLearningBase.) |
| Topology |
Gets or sets the state transition topology to be used when this learning
algorithm needs to create new models. Default is Forward.
|
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.
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| 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.) |
| ToString | Returns a string that represents the current object. (Inherited from Object.) |
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.) |
See Also