OneclassSupportVectorLearningTKernel Properties |
The OneclassSupportVectorLearningTKernel generic type exposes the following members.
Name | Description | |
---|---|---|
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.
(Inherited from BaseOneclassSupportVectorLearningTModel, TKernel, TInput.) | |
Lagrange |
Gets the value for the Lagrange multipliers
(alpha) for every observation vector.
(Inherited from BaseOneclassSupportVectorLearningTModel, TKernel, TInput.) | |
Model |
Gets or sets the classifier being learned.
(Inherited from BaseOneclassSupportVectorLearningTModel, TKernel, TInput.) | |
Nu |
Controls the number of outliers accepted by the algorithm. This
value provides an upper bound on the fraction of training errors
and a lower bound of the fraction of support vectors. Default is 0.5
(Inherited from BaseOneclassSupportVectorLearningTModel, TKernel, TInput.) | |
Shrinking |
Gets or sets a value indicating whether to use
shrinking heuristics during learning. Default is true.
(Inherited from BaseOneclassSupportVectorLearningTModel, TKernel, TInput.) | |
Token |
Gets or sets a cancellation token that can be used to
stop the learning algorithm while it is running.
(Inherited from BaseOneclassSupportVectorLearningTModel, TKernel, TInput.) | |
Tolerance |
Convergence tolerance. Default value is 1e-2.
(Inherited from BaseOneclassSupportVectorLearningTModel, TKernel, TInput.) | |
UseKernelEstimation |
Gets or sets whether initial values for some kernel parameters
should be estimated from the data, if possible. Default is true.
(Inherited from BaseOneclassSupportVectorLearningTModel, TKernel, TInput.) |