MatrixVectorProductOp
UseAccurateMethod
AAverageConditional(VectorGaussian, DistributionArray2D<Gaussian, Double>, Vector, PositiveDefiniteMatrix, DistributionStructArray2D<Gaussian, Double>)
AverageLogFactor(Vector, Matrix, Vector)
AverageLogFactor(VectorGaussian, Matrix, VectorGaussian)
AverageLogFactor(Vector, Matrix, VectorGaussian, Vector, PositiveDefiniteMatrix)
BAverageConditional(Vector, Matrix, VectorGaussian)
BAverageConditional(VectorGaussian, Matrix, VectorGaussian)
BAverageConditional(VectorGaussianMoments, Matrix, VectorGaussian)
BAverageConditional(VectorGaussian, Double[,], VectorGaussian)
BAverageConditional(VectorGaussianMoments, Double[,], VectorGaussian)
BAverageConditional(VectorGaussian, DistributionArray2D<Gaussian, Double>, VectorGaussian)
BAverageConditional(VectorGaussianMoments, DistributionArray2D<Gaussian, Double>, VectorGaussian)
BAverageLogarithm(Vector, Matrix, VectorGaussian)
BAverageLogarithm(VectorGaussian, Matrix, VectorGaussian)
BAverageLogarithm(VectorGaussianMoments, Matrix, VectorGaussian)
BMean(VectorGaussian, PositiveDefiniteMatrix, Vector)
BMeanInit(VectorGaussian)
BVariance(VectorGaussian, PositiveDefiniteMatrix)
BVarianceInit(VectorGaussian)
LogAverageFactor(VectorGaussian, VectorGaussian)
LogAverageFactor(Vector, Matrix, Vector)
LogAverageFactor(Vector, Matrix, VectorGaussian, Vector, PositiveDefiniteMatrix)
LogEvidenceRatio(Vector, Matrix, Vector)
LogEvidenceRatio(VectorGaussian, Matrix, VectorGaussian)
LogEvidenceRatio(VectorGaussian, Double[,], VectorGaussian)
LogEvidenceRatio(Vector, Matrix, VectorGaussian, Vector, PositiveDefiniteMatrix)
LogEvidenceRatio(VectorGaussian, DistributionArray2D<Gaussian, Double>, VectorGaussian)
ProductAverageConditional(Matrix, Vector, PositiveDefiniteMatrix, VectorGaussian)
ProductAverageConditional(Matrix, Vector, PositiveDefiniteMatrix, VectorGaussianMoments)
ProductAverageConditional(Double[,], Vector, PositiveDefiniteMatrix, VectorGaussian)
ProductAverageConditional(Double[,], Vector, PositiveDefiniteMatrix, VectorGaussianMoments)
ProductAverageConditional(DistributionArray2D<Gaussian, Double>, Vector, PositiveDefiniteMatrix, VectorGaussian)
ProductAverageConditional(DistributionArray2D<Gaussian, Double>, Vector, PositiveDefiniteMatrix, VectorGaussianMoments)
ProductAverageConditionalInit(Matrix)
ProductAverageLogarithm(Matrix, Vector, PositiveDefiniteMatrix, VectorGaussian)
ProductAverageLogarithm(Matrix, Vector, PositiveDefiniteMatrix, VectorGaussianMoments)
ProductAverageLogarithm(Double[,], Vector, PositiveDefiniteMatrix, VectorGaussian)
ProductAverageLogarithm(Double[,], Vector, PositiveDefiniteMatrix, VectorGaussianMoments)
ProductAverageLogarithmInit(Matrix)
netcoreapp2.0
namespace Microsoft.ML.Probabilistic.Factors
{
[Buffers(new[] { "BMean", "BVariance" })]
[FactorMethod(typeof(Factor), "Product", new[] { typeof(Matrix), typeof(Vector) })]
[FactorMethod(typeof(Factor), "Product", new[] { typeof(double[,]), typeof(Vector) })]
[Quality(QualityBand.Stable)]
public static class MatrixVectorProductOp
{
public static VectorGaussianMoments ProductAverageConditional(DistributionArray2D<Gaussian, double> A, Vector BMean, PositiveDefiniteMatrix BVariance, VectorGaussianMoments result);
}
}
.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