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HiddenGradientDescentLearningT Properties |
The HiddenGradientDescentLearningT generic type exposes the following members.
Name | Description | |
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![]() | CurrentIteration |
Gets or sets the number of performed iterations.
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![]() | 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.
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![]() | Iterations | Obsolete.
Please use MaxIterations instead.
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![]() | LearningRate |
Gets or sets the learning rate to use as the gradient
descent step size. Default value is 1e-1.
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![]() | MaxIterations |
Gets or sets the maximum number of iterations
performed by the learning algorithm.
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![]() | Model |
Gets or sets the model being trained.
(Inherited from BaseHiddenConditionalRandomFieldLearningT.) |
![]() | ParallelOptions |
Gets or sets the parallelization options for this algorithm.
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![]() | 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).
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![]() | Stochastic |
Gets or sets a value indicating whether this HiddenGradientDescentLearningT
should use stochastic gradient updates.
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![]() | 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 maximum change in the average log-likelihood
after an iteration of the algorithm used to detect convergence.
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