MultivariateKernelRegression Class

Multivariate non-linear regression using Kernels.

Inheritance Hierarchy

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

Syntax

[SerializableAttribute]
public class MultivariateKernelRegression : MultivariateKernelRegression<IKernel>

<SerializableAttribute>
Public Class MultivariateKernelRegression
	Inherits MultivariateKernelRegression(Of IKernel)

The MultivariateKernelRegression type exposes the following members.

Constructors

	Name	Description
	MultivariateKernelRegression	Initializes a new instance of the MultivariateKernelRegression class

Properties

	Name	Description
	BasisVectors	Gets or sets the original input data that is needed to compute the kernel (Gram) matrices for the regression. (Inherited from MultivariateKernelRegressionTKernel.)
	FeatureGrandMean	Gets or sets the grand mean of the data in feature space (to center samples). (Inherited from MultivariateKernelRegressionTKernel.)
	FeatureMeans	Gets or sets the means of the data in feature space (to center samples). (Inherited from MultivariateKernelRegressionTKernel.)
	Intercept	Obsolete. Gets or sets the intercept value for the regression. (Inherited from MultivariateKernelRegressionTKernel.)
	Kernel	Gets or sets the kernel function. (Inherited from MultivariateKernelRegressionTKernel.)
	Means	Gets or sets the mean values (to be subtracted from samples). (Inherited from MultivariateKernelRegressionTKernel.)
	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). (Inherited from MultivariateKernelRegressionTKernel.)
	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. (Inherited from MultivariateKernelRegressionTKernel.)

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. (Inherited from MultivariateKernelRegressionTKernel.)

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.)