BaseOneclassSupportVectorLearningTModel, TKernel, TInput Class

One-class Support Vector Machine Learning Algorithm.

Inheritance Hierarchy

SystemObject
  Accord.MachineLearning.VectorMachines.LearningBaseOneclassSupportVectorLearningTModel, TKernel, TInput
    Accord.MachineLearning.VectorMachines.LearningOneclassSupportVectorLearning
    Accord.MachineLearning.VectorMachines.LearningOneclassSupportVectorLearningTKernel
    Accord.MachineLearning.VectorMachines.LearningOneclassSupportVectorLearningTKernel, TInput

Namespace: Accord.MachineLearning.VectorMachines.Learning
Assembly: Accord.MachineLearning (in Accord.MachineLearning.dll) Version: 3.8.0

Syntax

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public abstract class BaseOneclassSupportVectorLearning<TModel, TKernel, TInput> : IUnsupervisedLearning<TModel, TInput, bool>
where TModel : Object, ISupportVectorMachine<TInput>
where TKernel : Object, IKernel<TInput>

Public MustInherit Class BaseOneclassSupportVectorLearning(Of TModel As {Object, ISupportVectorMachine(Of TInput)}, TKernel As {Object, IKernel(Of TInput)}, TInput)
	Implements IUnsupervisedLearning(Of TModel, TInput, Boolean)

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Type Parameters

TModel
TKernel
TInput

The BaseOneclassSupportVectorLearningTModel, TKernel, TInput type exposes the following members.

Constructors

	Name	Description
	BaseOneclassSupportVectorLearningTModel, TKernel, TInput	Constructs a new one-class support vector learning algorithm.
	BaseOneclassSupportVectorLearningTModel, TKernel, TInput(TModel)	Constructs a new one-class support vector learning algorithm.
	BaseOneclassSupportVectorLearningTModel, TKernel, TInput(ISupportVectorMachineTInput, TInput)	Obsolete.

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Properties

	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.
	Lagrange	Gets the value for the Lagrange multipliers (alpha) for every observation vector.
	Model	Gets or sets the classifier being learned.
	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
	Shrinking	Gets or sets a value indicating whether to use shrinking heuristics during learning. Default is true.
	Token	Gets or sets a cancellation token that can be used to stop the learning algorithm while it is running.
	Tolerance	Convergence tolerance. Default value is 1e-2.
	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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Methods

	Name	Description
	Create	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.
	Equals	Determines whether the specified object is equal to the current object. (Inherited from Object.)
	Finalize	Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object.)
	GetHashCode	Serves as the default hash function. (Inherited from Object.)
	GetType	Gets the Type of the current instance. (Inherited from Object.)
	Learn	Learns a model that can map the given inputs to the desired outputs.
	MemberwiseClone	Creates a shallow copy of the current Object. (Inherited from Object.)
	Run	Obsolete. Obsolete.
	ToString	Returns a string that represents the current object. (Inherited from Object.)

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Extension Methods

	Name	Description
	HasMethod	Checks whether an object implements a method with the given name. (Defined by ExtensionMethods.)
	IsEqual	Compares two objects for equality, performing an elementwise comparison if the elements are vectors or matrices. (Defined by Matrix.)
	To(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.)
	ToT	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.)

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Reference

Accord.MachineLearning.VectorMachines.Learning Namespace

BaseOneclassSupportVectorLearningAddLanguageSpecificTextSet("LSTCE1C99BF_0?cs=&lt;|vb=(Of |cpp=&lt;|fs=&lt;'|nu=(");TModel, TKernel, TInputAddLanguageSpecificTextSet("LSTCE1C99BF_1?cs=&gt;|vb=)|cpp=&gt;|fs=&gt;|nu=)"); Class

Type Parameters

Reference

BaseOneclassSupportVectorLearningTModel, TKernel, TInput Class