Click or drag to resize
Accord.NET (logo)

BaumWelchLearning Properties

The BaumWelchLearning type exposes the following members.

Properties
  NameDescription
Public propertyConvergence
Gets or sets convergence parameters.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.)
Public propertyCurrentIteration
Gets or sets the number of performed iterations.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.)
Public propertyEmissions
Gets or sets the function that initializes the emission distributions in the hidden Markov Models.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.)
Public propertyFittingOptions
Gets or sets the distribution fitting options to use when estimating distribution densities during learning.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.)
Public propertyHasConverged
Gets or sets whether the algorithm has converged.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.)
Public propertyIterations Obsolete.
Please use MaxIterations instead.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.)
Public propertyLogGamma
Gets the Gamma matrix of log probabilities created during the last iteration of the Baum-Welch learning algorithm.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.)
Public propertyLogKsi
Gets the Ksi matrix of log probabilities created during the last iteration of the Baum-Welch learning algorithm.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.)
Public propertyLogLikelihood
Gets the log-likelihood of the model at the last iteration.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.)
Public propertyLogWeights
Gets the sample weights in the last iteration of the Baum-Welch learning algorithm.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.)
Public propertyMaxIterations
Gets or sets the maximum number of iterations performed by the learning algorithm.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.)
Public propertyModel
Gets or sets the model being trained.
(Inherited from BaseHiddenMarkovModelLearningTModel, TObservation.)
Public propertyNumberOfStates
Gets or sets the number of states to be used when this learning algorithm needs to create new models.
(Inherited from BaseHiddenMarkovModelLearningTModel, TObservation.)
Public propertyNumberOfSymbols
Gets or sets the number of symbols that should be used whenever this learning algorithm needs to create a new model. This property must be set before learning.
Protected propertyObservations
Gets all observations as a single vector.
(Inherited from BaseBaumWelchLearningTModel, TDistribution, TObservation, TOptions.)
Public propertyParallelOptions
Gets or sets the parallelization options for this algorithm.
(Inherited from ParallelLearningBase.)
Public propertyToken
Gets or sets a cancellation token that can be used to cancel the algorithm while it is running.
(Inherited from ParallelLearningBase.)
Public propertyTolerance
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.)
Public propertyTopology
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.)
Top
See Also