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BaseSupportVectorRegressionTModel, TKernel, TInput Class

Base class for SupportVectorMachine regression learning algorithms.
Inheritance Hierarchy
  Accord.MachineLearning.VectorMachines.LearningBaseSupportVectorRegressionTModel, TKernel, TInput
    Accord.MachineLearning.VectorMachines.LearningBaseFanChenLinSupportVectorRegressionTModel, TKernel, TInput
    Accord.MachineLearning.VectorMachines.LearningBaseLinearRegressionCoordinateDescentTModel, TKernel, TInput
    Accord.MachineLearning.VectorMachines.LearningBaseLinearRegressionNewtonMethodTModel, TKernel, TInput
    Accord.MachineLearning.VectorMachines.LearningBaseSequentialMinimalOptimizationRegressionTModel, TKernel, TInput

Namespace:  Accord.MachineLearning.VectorMachines.Learning
Assembly:  Accord.MachineLearning (in Accord.MachineLearning.dll) Version: 3.8.0
public abstract class BaseSupportVectorRegression<TModel, TKernel, TInput> : ISupervisedLearning<TModel, TInput, double>
where TModel : SupportVectorMachine<TKernel, TInput>, ISupportVectorMachine<TInput>
where TKernel : Object, IKernel<TInput>
where TInput : ICloneable
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Type Parameters


The BaseSupportVectorRegressionTModel, TKernel, TInput 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.
Public methodComputeError Obsolete.
Protected methodCreate
Creates an instance of the model to be learned. Inheritors of this abstract class must define this method so new models can be created from the training data.
Public methodEquals
Determines whether the specified object is equal to the current object.
(Inherited from Object.)
Protected methodFinalize
Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection.
(Inherited from Object.)
Public methodGetHashCode
Serves as the default hash function.
(Inherited from Object.)
Public methodGetType
Gets the Type of the current instance.
(Inherited from Object.)
Protected methodInnerRun
Runs the learning algorithm.
Public methodLearn
Learns a model that can map the given inputs to the given outputs.
Protected methodMemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
Public methodRun Obsolete.
Public methodToString
Returns a string that represents the current object.
(Inherited from Object.)
Extension Methods
Public Extension MethodHasMethod
Checks whether an object implements a method with the given name.
(Defined by ExtensionMethods.)
Public Extension MethodIsEqual
Compares two objects for equality, performing an elementwise comparison if the elements are vectors or matrices.
(Defined by Matrix.)
Public Extension MethodTo(Type)Overloaded.
Converts an object into another type, irrespective of whether the conversion can be done at compile time or not. This can be used to convert generic types to numeric types during runtime.
(Defined by ExtensionMethods.)
Public Extension MethodToTOverloaded.
Converts an object into another type, irrespective of whether the conversion can be done at compile time or not. This can be used to convert generic types to numeric types during runtime.
(Defined by ExtensionMethods.)
See Also