ExpOp
ForceProper
QuadratureIterations
QuadratureNodeCount
QuadratureShift
UseRandomDamping
ExpOp()
AverageLogFactor()
AverageLogFactor(Double, Double)
DAverageConditional(Double)
DAverageConditional(Gamma, Gaussian, Gaussian)
DAverageConditional(GammaPower, Gaussian, Gaussian)
DAverageLogarithm(Double)
DAverageLogarithm(Gamma, Gaussian, Gaussian)
DAverageLogarithm(Gamma, NonconjugateGaussian, NonconjugateGaussian)
DNonconjugateAverageLogarithm(Gamma, Gaussian, NonconjugateGaussian)
ExpAverageConditional(Gamma, Gaussian, Gaussian)
ExpAverageConditional(GammaPower, Gaussian, Gaussian)
ExpAverageConditionalInit(Gaussian)
ExpAverageLogarithm(Gaussian)
ExpAverageLogarithm(NonconjugateGaussian)
ExpAverageLogarithm(Gaussian, GammaPower)
ExpAverageLogarithmInit()
LogAverageFactor_slow(Gamma, Gaussian)
LogAverageFactor(Double, Double)
LogAverageFactor(Double, Gaussian)
LogAverageFactor(Gamma, Gaussian, Gaussian)
LogAverageFactor(GammaPower, Gaussian, Gaussian)
LogAverageFactor(CanGetLogProb<Double>, Double)
LogEvidenceRatio(Double, Double)
LogEvidenceRatio(Double, Gaussian)
LogEvidenceRatio(Gamma, Gaussian, Gamma, Gaussian)
LogEvidenceRatio(GammaPower, Gaussian, GammaPower, Gaussian)
netcoreapp2.0
namespace Microsoft.ML.Probabilistic.Factors
{
[FactorMethod(typeof(Math), "Exp", new[] { typeof(double) }, Default = true)]
[Quality(QualityBand.Stable)]
public class ExpOp
{
public static double LogEvidenceRatio(Gamma exp, Gaussian d, [Fresh] Gamma to_exp, Gaussian to_d);
}
}
.NET | 5.06.07.08.09.010.0 |
---|---|
.NET Core | 2.02.12.23.03.1 |
.NET Framework | 4.6.14.6.24.74.7.14.7.24.84.8.1 |
.NET Standard | 2.02.1 |
Information specific to netcoreapp2.0 | |
Assembly | Microsoft.ML.Probabilistic , Version=0.4.2403.801, PublicKeyToken=e4813102a62778da |
Referencing | Your project needs a package reference to |
Package | Microsoft.ML.Probabilistic (0.4.2403.801) netstandard2.0 |
Platform Restrictions | This framework does not have platform annotations. |
- Built-in API
- Package-provided API