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    Class SquaredExponential

    Squared Exponential kernel function: k(x,y) = exp(-0.5*(x-y)^2/exp(2*logLength))

    Inheritance
    Object
    KernelFunction
    SquaredExponential
    Implements
    IKernelFunctionWithParams
    IKernelFunction
    Inherited Members
    KernelFunction.thetaNames
    KernelFunction.thetaValues
    KernelFunction.thetaName2Index
    KernelFunction.HyperNames
    KernelFunction.EvaluateX1X2(Vector, Vector)
    KernelFunction.EvaluateX1X2(Vector, Vector, Vector)
    KernelFunction.EvaluateX(Vector)
    KernelFunction.EvaluateX(Vector, Vector)
    KernelFunction.Item[String]
    KernelFunction.NameToIndex(String)
    KernelFunction.IndexToName(Int32)
    KernelFunction.ThetaCount
    KernelFunction.Write(StreamWriter)
    KernelFunction.Read(StreamReader)
    KernelFunction.Cholesky(IKernelFunction, Dictionary<Int32, Vector>)
    Object.Equals(Object, Object)
    Object.GetType()
    Object.MemberwiseClone()
    Object.ReferenceEquals(Object, Object)
    Namespace: Microsoft.ML.Probabilistic.Distributions.Kernels
    Assembly: Microsoft.ML.Probabilistic.dll
    Syntax
    [Serializable]
    [DataContract]
    public class SquaredExponential : KernelFunction, IKernelFunctionWithParams, IKernelFunction

    Constructors

    SquaredExponential()

    Constructs the kernel k(x,y) = exp(- 0.5*(x-y)^2)

    Declaration
    public SquaredExponential()

    SquaredExponential(Double)

    Constructs the kernel k(x,y) = exp(- 0.5*(x-y)^2/exp(2*logLength))

    Declaration
    public SquaredExponential(double logLengthScale)
    Parameters
    Type Name Description
    Double logLengthScale

    SquaredExponential(Double, Double)

    Constructs the kernel k(x,y) = exp(2logSignalSD - 0.5(x-y)^2/exp(2*logLength))

    Declaration
    [Construction(new string[]{"LogLengthScale", "LogSignalSD"})]
    public SquaredExponential(double logLengthScale, double logSignalSD)
    Parameters
    Type Name Description
    Double logLengthScale

    Log length

    Double logSignalSD

    Log signal variance

    Properties

    Item[Int32]

    Sets or gets a log hyper-parameter by index

    Declaration
    public override double this[int index] { get; set; }
    Parameters
    Type Name Description
    Int32 index
    Property Value
    Type Description
    Double
    Overrides
    KernelFunction.Item[Int32]

    LogLengthScale

    Sets/gets log of the length scale

    Declaration
    public double LogLengthScale { get; set; }
    Property Value
    Type Description
    Double

    LogSignalSD

    Gets/sets log of the signal variance

    Declaration
    public double LogSignalSD { get; set; }
    Property Value
    Type Description
    Double

    TypeVersion

    The static version for the derived class

    Declaration
    public override int TypeVersion { get; }
    Property Value
    Type Description
    Int32
    Overrides
    KernelFunction.TypeVersion

    Methods

    Equals(Object)

    Declaration
    public override bool Equals(object obj)
    Parameters
    Type Name Description
    Object obj
    Returns
    Type Description
    Boolean
    Overrides
    Object.Equals(Object)

    EvaluateX(Vector, ref Vector, ref Vector)

    Evaluates the kernel for a single vector (which is used for both slots)

    Declaration
    public override double EvaluateX(Vector x, ref Vector xDeriv, ref Vector logThetaDeriv)
    Parameters
    Type Name Description
    Vector x

    Vector

    Vector xDeriv

    Derivative of the kernel value with respect to x

    Vector logThetaDeriv

    Derivative of the kernel value with respect to the log hyper-parameters

    Returns
    Type Description
    Double
    Overrides
    KernelFunction.EvaluateX(Vector, ref Vector, ref Vector)

    EvaluateX1X2(Vector, Vector, ref Vector, ref Vector)

    Evaluates the kernel for a pair of vectors

    Declaration
    public override double EvaluateX1X2(Vector x1, Vector x2, ref Vector x1Deriv, ref Vector logThetaDeriv)
    Parameters
    Type Name Description
    Vector x1

    First vector

    Vector x2

    Second vector

    Vector x1Deriv

    Derivative of the kernel value with respect to x1 input vector

    Vector logThetaDeriv

    Derivative of the kernel value with respect to the log hyper-parameters

    Returns
    Type Description
    Double
    Overrides
    KernelFunction.EvaluateX1X2(Vector, Vector, ref Vector, ref Vector)

    GetHashCode()

    Declaration
    public override int GetHashCode()
    Returns
    Type Description
    Int32
    Overrides
    Object.GetHashCode()

    ToString()

    Declaration
    public override string ToString()
    Returns
    Type Description
    String
    Overrides
    Object.ToString()

    Operators

    Equality(SquaredExponential, SquaredExponential)

    Checks if left object is equal to right.

    Declaration
    public static bool operator ==(SquaredExponential left, SquaredExponential right)
    Parameters
    Type Name Description
    SquaredExponential left
    SquaredExponential right
    Returns
    Type Description
    Boolean

    Inequality(SquaredExponential, SquaredExponential)

    Checks if left object is equal to right.

    Declaration
    public static bool operator !=(SquaredExponential left, SquaredExponential right)
    Parameters
    Type Name Description
    SquaredExponential left
    SquaredExponential right
    Returns
    Type Description
    Boolean

    Implements

    IKernelFunctionWithParams
    IKernelFunction
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