Class GaussianProcess
A base class for Gaussian process distributions
Inherited Members
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
GetHashCode()
Declaration
public override int GetHashCode()
Returns
Type | Description |
---|---|
Int32 |
Overrides
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
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 |