Sigmoid Class

Sigmoid Kernel.

Inheritance Hierarchy

SystemObject
  Accord.Statistics.KernelsKernelBaseDouble
    Accord.Statistics.KernelsKernelBase
      Accord.Statistics.KernelsSigmoid

Namespace: Accord.Statistics.Kernels
Assembly: Accord.Statistics (in Accord.Statistics.dll) Version: 3.8.0

Syntax

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[SerializableAttribute]
public sealed class Sigmoid : KernelBase, 
	IKernel, IKernel<double[]>, ICloneable, IEstimable, 
	IEstimable<double[]>, IKernel<Sparse<double>>, 
	IDistance<Sparse<double>>, IDistance<Sparse<double>, Sparse<double>>

<SerializableAttribute>
Public NotInheritable Class Sigmoid
	Inherits KernelBase
	Implements IKernel, IKernel(Of Double()), 
	ICloneable, IEstimable, IEstimable(Of Double()), IKernel(Of Sparse(Of Double)), 
	IDistance(Of Sparse(Of Double)), IDistance(Of Sparse(Of Double), Sparse(Of Double))

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The Sigmoid type exposes the following members.

Constructors

	Name	Description
	Sigmoid	Constructs a Sigmoid kernel.
	Sigmoid(Double, Double)	Constructs a Sigmoid kernel.

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Properties

	Name	Description
	Alpha	Gets or sets the kernel's alpha parameter.
	Constant	Gets or sets the kernel's constant term.

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Methods

	Name	Description
	Clone	Creates a new object that is a copy of the current instance.
	Distance(TInput, TInput)	Computes the squared distance in feature space between two points given in input space. (Inherited from KernelBaseTInput.)
	Distance(SparseDouble, SparseDouble)	Computes the squared distance in feature space between two points given in input space.
	Equals	Determines whether the specified object is equal to the current object. (Inherited from Object.)
	Estimate(Double)	Estimates suitable values for the sigmoid kernel by exploring the response area of the tanh function.
	Estimate(Double, Int32, DoubleRange)	Estimates suitable values for the sigmoid kernel by exploring the response area of the tanh function.
	Function(Double)	Sigmoid kernel function.
	Function(Double, Double)	Sigmoid kernel function. (Overrides KernelBaseTInputFunction(TInput, TInput).)
	Function(SparseDouble, SparseDouble)	Sigmoid kernel function.
	GetHashCode	Serves as the default hash function. (Inherited from Object.)
	GetType	Gets the Type of the current instance. (Inherited from Object.)
	Products	Computes the set of all distances between all points in a random subset of the data.
	ToString	Returns a string that represents the current object. (Inherited from Object.)

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Extension Methods

	Name	Description
	Distance	Computes the kernel distance for a kernel function even if it doesn't implement the IDistance interface. Can be used to check the proper implementation of the distance function. (Defined by Tools.)
	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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Remarks

Sigmoid kernel of the form k(x,z) = tanh(a * x'z + c). Sigmoid kernels are only conditionally positive definite for some values of a and c, and therefore may not induce a reproducing kernel Hilbert space. However, they have been successfully used in practice (Schölkopf and Smola, 2002).

Reference

Accord.Statistics.Kernels Namespace