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BaseSupportVectorRegressionTModel, TKernel, TInput Properties

The BaseSupportVectorRegressionTModel, TKernel, TInput generic type exposes the following members.

Protected propertyC
Gets or sets the cost values associated with each input vector.
Public propertyComplexity
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.
Public propertyEpsilon
Insensitivity zone ε. Increasing the value of ε can result in fewer support vectors in the created model. Default value is 1e-3.
Protected propertyInputs
Gets or sets the input vectors for training.
Protected propertyIsLinear
Gets whether the machine to be learned has a Linear kernel.
Public propertyKernel
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.
Public propertyModel
Gets the machine to be taught.
Protected propertyOutputs
Gets or sets the output values for each calibration vector.
Public propertyToken
Gets or sets a cancellation token that can be used to stop the learning algorithm while it is running.
Public propertyUseComplexityHeuristic
Gets or sets a value indicating whether the Complexity parameter C should be computed automatically by employing an heuristic rule. Default is false.
Public propertyUseKernelEstimation
Gets or sets whether initial values for some kernel parameters should be estimated from the data, if possible. Default is true.
Public propertyWeights
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.
See Also