BaumWelchLearningTDistribution, TObservation, TOptions Class |
Namespace: Accord.Statistics.Models.Markov.Learning
public class BaumWelchLearning<TDistribution, TObservation, TOptions> : BaseBaumWelchLearningOptions<HiddenMarkovModel<TDistribution, TObservation>, TDistribution, TObservation, TOptions>, IConvergenceLearning where TDistribution : Object, IFittableDistribution<TObservation, TOptions> where TOptions : class, new(), IFittingOptions
The BaumWelchLearningTDistribution, TObservation, TOptions type exposes the following members.
Name | Description | |
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BaumWelchLearningTDistribution, TObservation, TOptions |
Initializes a new instance of the BaumWelchLearningTDistribution, TObservation, TOptions class.
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BaumWelchLearningTDistribution, TObservation, TOptions(HiddenMarkovModelTDistribution, TObservation) |
Initializes a new instance of the BaumWelchLearningTDistribution, TObservation, TOptions class.
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Name | Description | |
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Convergence |
Gets or sets convergence parameters.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.) | |
CurrentIteration |
Gets or sets the number of performed iterations.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.) | |
Emissions |
Gets or sets the function that initializes the emission
distributions in the hidden Markov Models.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.) | |
FittingOptions |
Gets or sets the distribution fitting options
to use when estimating distribution densities
during learning.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.) | |
HasConverged |
Gets or sets whether the algorithm has converged.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.) | |
Iterations | Obsolete.
Please use MaxIterations instead.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.) | |
LogGamma |
Gets the Gamma matrix of log probabilities created during
the last iteration of the Baum-Welch learning algorithm.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.) | |
LogKsi |
Gets the Ksi matrix of log probabilities created during
the last iteration of the Baum-Welch learning algorithm.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.) | |
LogLikelihood |
Gets the log-likelihood of the model at the last iteration.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.) | |
LogWeights |
Gets the sample weights in the last iteration of the
Baum-Welch learning algorithm.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.) | |
MaxIterations |
Gets or sets the maximum number of iterations
performed by the learning algorithm.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.) | |
Model |
Gets or sets the model being trained.
(Inherited from BaseHiddenMarkovModelLearningTModel, TObservation.) | |
NumberOfStates |
Gets or sets the number of states to be used when this
learning algorithm needs to create new models.
(Inherited from BaseHiddenMarkovModelLearningTModel, TObservation.) | |
Observations |
Gets all observations as a single vector.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.) | |
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.) | |
Tolerance |
Gets or sets the maximum change in the average log-likelihood
after an iteration of the algorithm used to detect convergence.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.) | |
Topology |
Gets or sets the state transition topology to be used when this learning
algorithm needs to create new models. Default is Forward.
(Inherited from BaseHiddenMarkovModelLearningTModel, TObservation.) |
Name | Description | |
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ComputeForwardBackward |
Computes the forward and backward probabilities matrices
for a given observation referenced by its index in the
input training data.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.) | |
ComputeKsi |
Computes the ksi matrix of probabilities for a given observation
referenced by its index in the input training data.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.) | |
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.
(Overrides BaseHiddenMarkovModelLearningTModel, TObservationCreate(TObservation).) | |
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.) | |
Fit |
Fits one emission distribution. This method can be override in a
base class in order to implement special fitting options.
(Inherited from BaseBaumWelchLearningOptionsTModel, TDistribution, TObservation, TOptions.) | |
GetHashCode | Serves as the default hash function. (Inherited from Object.) | |
GetType | Gets the Type of the current instance. (Inherited from Object.) | |
Learn |
Learns a model that can map the given inputs to the desired outputs.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.) | |
MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object.) | |
ToString | Returns a string that represents the current object. (Inherited from Object.) | |
UpdateEmissions |
Updates the emission probability matrix.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.) |
Name | Description | |
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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.) |