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BaseAveragedStochasticGradientDescentTModel, TKernel, TInput, TLoss Properties |
The BaseAveragedStochasticGradientDescentTModel, TKernel, TInput, TLoss generic type exposes the following members.
Properties| Name | Description | |
|---|---|---|
 | CurrentEpoch |
Gets or sets the current epoch counter.
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| Iterations | Obsolete.
Please use MaxIterations instead.
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| Kernel |
Gets or sets the kernel function use to create a
kernel Support Vector Machine.
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| Lambda |
Gets or sets the lambda regularization term. Default is 0.5.
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| LearningRate |
Gets or sets the learning rate for the SGD algorithm.
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| Loss |
Gets or sets the loss function to be used.
Default is to use the LogisticLoss.
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| MaxIterations |
Gets or sets the number of iterations that should be
performed by the algorithm when calling Learn(TInput, Boolean, Double).
Default is 0 (iterate until convergence).
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| Model |
Gets or sets the classifier being learned.
(Inherited from BinaryLearningBaseTModel, TInput.) |
| ParallelOptions |
Gets or sets the parallelization options for this algorithm.
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| Token |
Gets or sets a cancellation token that can be used
to cancel the algorithm while it is running.
(Overrides BinaryLearningBaseTModel, TInputToken.) |
| Tolerance |
Gets or sets the maximum relative change in the watched value
after an iteration of the algorithm used to detect convergence.
Default is 1e-3. If set to 0, the loss will not be computed
during learning and execution will be faster.
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See Also