Class GaussianProcess

A base class for Gaussian process distributions

Inheritance

Object

GaussianProcess

Implements

IGaussianProcess

Sampleable<IFunction>

Inherited Members

Object.Equals(Object, Object)

Object.GetType()

Object.MemberwiseClone()

Object.ReferenceEquals(Object, Object)

Namespace: Microsoft.ML.Probabilistic.Distributions

Assembly: Microsoft.ML.Probabilistic.dll

Syntax

[Serializable]
[DataContract]
public class GaussianProcess : IGaussianProcess, Sampleable<IFunction>

Constructors

GaussianProcess(IFunction, IKernelFunction)

Constructor

Declaration

[Construction(new string[]{"mean", "kernel"})]
public GaussianProcess(IFunction mean, IKernelFunction kernel)

Parameters

Type	Name	Description
IFunction	mean	Mean function
IKernelFunction	kernel	Kernel function

Fields

kernel

Covariance function

Declaration

[DataMember]
public IKernelFunction kernel

Field Value

Type	Description
IKernelFunction

mean

Mean function

Declaration

[DataMember]
public IFunction mean

Field Value

Type	Description
IFunction

Methods

Covariance(Vector, Vector)

Predictive covariance at a given pair of points

Declaration

public double Covariance(Vector x, Vector y)

Parameters

Type	Name	Description
Vector	x
Vector	y

Returns

Type	Description
Double

Covariance(IList<Vector>)

Predictive coariance at a given list of points

Declaration

public PositiveDefiniteMatrix Covariance(IList<Vector> XList)

Parameters

Type	Name	Description
IList<Vector>	XList	List of inputs

Returns

Type	Description
PositiveDefiniteMatrix	Predictive covariance

Equals(Object)

Declaration

public override bool Equals(object obj)

Parameters

Type	Name	Description
Object	obj

Returns

Type	Description
Boolean

Overrides

Object.Equals(Object)

GetHashCode()

Declaration

public override int GetHashCode()

Returns

Type	Description
Int32

Overrides

Object.GetHashCode()

Joint(IList<Vector>)

Predictive distribution at a given list of points

Declaration

public VectorGaussian Joint(IList<Vector> XList)

Parameters

Type	Name	Description
IList<Vector>	XList	List of inputs

Returns

Type	Description
VectorGaussian	Predictive distribution

Marginal(Vector)

Predictive distribution at a given point

Declaration

public Gaussian Marginal(Vector X)

Parameters

Type	Name	Description
Vector	X	Input

Returns

Type	Description
Gaussian	Predictive distribution

Mean(Vector)

Mean at a given point

Declaration

public double Mean(Vector X)

Parameters

Type	Name	Description
Vector	X

Returns

Type	Description
Double

Mean(IList<Vector>)

Mean at a given list of points

Declaration

public Vector Mean(IList<Vector> XList)

Parameters

Type	Name	Description
IList<Vector>	XList	List of inputs

Returns

Type	Description
Vector	Predictive mean vector

Sample()

This base class just returns the mean function

Declaration

public IFunction Sample()

Returns

Type	Description
IFunction

Sample(IFunction)

This base class just returns the mean function

Declaration

public IFunction Sample(IFunction result)

Parameters

Type	Name	Description
IFunction	result

Returns

Type	Description
IFunction

ToString()

Declaration

public override string ToString()

Returns

Type	Description
String

Overrides

Object.ToString()

Variance(Vector)

Predictive Variance at a given point

Declaration

public double Variance(Vector X)

Parameters

Type	Name	Description
Vector	X	Input

Returns

Type	Description
Double	Predictive variance

Implements

IGaussianProcess

Sampleable<T>