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BaseSupportVectorRegressionTModel, TKernel, TInput Properties |
The BaseSupportVectorRegressionTModel, TKernel, TInput generic type exposes the following members.
Properties| Name | Description | |
|---|---|---|
 | C |
Gets or sets the cost values associated with each input vector.
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 | Complexity |
Complexity (cost) parameter C. Increasing the value of C forces the creation
of a more accurate model that may not generalize well. If this value is not
set and UseComplexityHeuristic is set to true, the framework
will automatically guess a value for C. If this value is manually set to
something else, then UseComplexityHeuristic will be automatically
disabled and the given value will be used instead.
|
| Epsilon |
Insensitivity zone ε. Increasing the value of ε can result in fewer
support vectors in the created model. Default value is 1e-3.
|
| Inputs |
Gets or sets the input vectors for training.
|
| IsLinear |
Gets whether the machine to be learned
has a Linear kernel.
|
| Kernel |
Gets or sets the kernel function use to create a
kernel Support Vector Machine. If this property
is set, UseKernelEstimation will be
set to false.
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| Model |
Gets the machine to be taught.
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| Outputs |
Gets or sets the output values for each calibration vector.
|
| Token |
Gets or sets a cancellation token that can be used to
stop the learning algorithm while it is running.
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| UseComplexityHeuristic |
Gets or sets a value indicating whether the Complexity parameter C
should be computed automatically by employing an heuristic rule.
Default is false.
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| UseKernelEstimation |
Gets or sets whether initial values for some kernel parameters
should be estimated from the data, if possible. Default is true.
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| Weights |
Gets or sets the individual weight of each sample in the training set. If set
to null, all samples will be assumed equal weight. Default is null.
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See Also