MultivariateKernelRegressionTKernel Class

Multivariate non-linear regression using Kernels.

Inheritance Hierarchy

SystemObject
  Accord.MachineLearningTransformBaseDouble, Double
    Accord.MachineLearningMultipleTransformBaseDouble, Double
      Accord.Statistics.Models.RegressionMultivariateKernelRegressionTKernel
        Accord.Statistics.Models.RegressionMultivariateKernelRegression

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

Syntax

Copy

[SerializableAttribute]
public class MultivariateKernelRegression<TKernel> : MultipleTransformBase<double[], double>
where TKernel : Object, IKernel<double[]>

<SerializableAttribute>
Public Class MultivariateKernelRegression(Of TKernel As {Object, IKernel(Of Double())})
	Inherits MultipleTransformBase(Of Double(), Double)

Request Example View Source

Type Parameters

TKernel: The kernel function.

The MultivariateKernelRegressionTKernel type exposes the following members.

Constructors

	Name	Description
	MultivariateKernelRegressionTKernel	Initializes a new instance of the MultivariateKernelRegressionTKernel class

Top

Properties

	Name	Description
	BasisVectors	Gets or sets the original input data that is needed to compute the kernel (Gram) matrices for the regression.
	FeatureGrandMean	Gets or sets the grand mean of the data in feature space (to center samples).
	FeatureMeans	Gets or sets the means of the data in feature space (to center samples).
	Intercept	Obsolete. Gets or sets the intercept value for the regression.
	Kernel	Gets or sets the kernel function.
	Means	Gets or sets the mean values (to be subtracted from samples).
	NumberOfInputs	Gets the number of inputs accepted by the model. (Inherited from TransformBaseTInput, TOutput.)
	NumberOfOutputs	Gets the number of outputs generated by the model. (Inherited from TransformBaseTInput, TOutput.)
	StandardDeviations	Gets or sets the standard deviations (to be divided from samples).
	Weights	Gets or sets the linear weights of the regression model. The intercept term is not stored in this vector, but is instead available through the Intercept property.

Top

Methods

	Name	Description
	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.)
	MemberwiseClone	Creates a shallow copy of the current Object. (Inherited from Object.)
	ToString	Returns a string that represents the current object. (Inherited from Object.)
	Transform(TInput)	Applies the transformation to an input, producing an associated output. (Inherited from MultipleTransformBaseTInput, TOutput.)
	Transform(TInput)	Applies the transformation to a set of input vectors, producing an associated set of output vectors. (Inherited from MultipleTransformBaseTInput, TOutput.)
	Transform(TInput, TOutput)	Applies the transformation to an input, producing an associated output. (Inherited from MultipleTransformBaseTInput, TOutput.)
	Transform(Double, Double)	Applies the transformation to an input, producing an associated output. (Overrides MultipleTransformBaseTInput, TOutputTransform(TInput, TOutput).)

Top

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.)

Top

Reference

Accord.Statistics.Models.Regression Namespace

MultivariateKernelRegressionAddLanguageSpecificTextSet("LST7A79E134_0?cs=&lt;|vb=(Of |cpp=&lt;|fs=&lt;'|nu=(");TKernelAddLanguageSpecificTextSet("LST7A79E134_1?cs=&gt;|vb=)|cpp=&gt;|fs=&gt;|nu=)"); Class

Type Parameters

Reference

MultivariateKernelRegressionTKernel Class