L
SparkSquareMatrix
L1Updater
optimization
LIN
TransferFunctions
LSSVMCommittee
svm
LSSVMLinearSolver
optimization
LSSVMModel
svm
LSSVMSparkModel
svm
LUAcc
bLU
Label
utils
LaplaceBinaryGPC
gp
LaplaceCovFunc
kernels
LaplacePosteriorMode
optimization
LaplacianKernel
kernels
LazyNeuralStack
neuralnets
LeafParameter
statespace
LeafState
statespace
LeastSquaresGradient
optimization
LeastSquaresSVMGradient
optimization
LegendreBasisGenerator
analysis
Likelihood
probability
LikelihoodModel
probability
LinearKernel
kernels
LinearModel
models POMP
LinearPDEKernel
kernels
LinearTrendESGPrior
bayes
LinearTrendGaussianPrior
bayes
LinearTrendStochasticPrior
bayes
LocalSVMKernel
kernels
LocalScalarKernel
kernels
LocallyStationaryKernel
kernels
LogGaussianCox
POMP
LogGaussianProcessModel
gp
LogLikelihood
POMP
LogisticGLM
lm
LogisticGradient
optimization
Loglikelihood
generalDLM
l
CoRegGraphKernel
l1
Parameters
l2
Parameters
lambda
VectorSELU Wavelet
laplacian
RadialBasis
laplacianBasis
RadialBasis
layerCreationContext
api
layerFactories
NeuralStackFactory
layerParameters
NeuralStack
layerType
Tanh
layers
tensorflow
lcm
PartitionedVectorField VectorField fieldTuple2
learn
ParameterizedLearner SubsampledDualLSSVM CommitteeModel AbstractGPClassification GPCommitteeRegression GenericGLM AutoEncoder CommitteeNetwork FeedForwardNetwork GenericAutoEncoder GenericFFNeuralNet DLSSVM LSSVMCommittee LSSVMSparkModel
left
BranchParameter BranchState
legendre
utils
len
BinaryClassificationMetrics BinaryClassificationMetricsSpark MultiRegressionMetrics RegressionMetrics RegressionMetricsSpark
length
BinaryClassificationMetrics BinaryClassificationMetricsSpark MultiRegressionMetrics RegressionMetrics RegressionMetricsSpark Parameters SdeParameter StateParameter
lengthScales
RadialBasis
likelihood
FilterOut LaplacePosteriorMode ApproxBayesComputation JointProbabilityScheme RejectionSamplingScheme
lin
TransferFunctions
link
StateSpaceModel
ll
MetropState PfState MetropolisState
llFilter
ParticleFilter
lm
models
localField
NeuralLayer
log1pExp
utils
logLikelihood
AbstractGPClassification AbstractGPRegressionModel ESGPModel MetropolisHastings ParticleMetropolis ParticleMetropolisHastings AbstractSTPRegressionModel AdaptiveHyperParameterMCMC
logLikelihoodF
GeneralMetropolisHastings
logNormalizer
BlockedMultiVariateGaussian BlockedMultivariateStudentsT Erlang Kumaraswamy MVGaussian MatrixNormal MatrixT MixtureDistribution MultivariateStudentsT MultivariateUniform SkewSymmDistribution TruncatedGaussian UnivariateStudentsT
logTransition
MetropolisHastings ParticleMetropolis ParticleMetropolisHastings
logTransitionProbability
GeneralMetropolisHastings HamiltonianMetropolis
log_e
QuadraticRenyiEntropy
loga
Kumaraswamy
logarithmicScale
ModelTuner
logb
Kumaraswamy
logger
DynaMLPipe KernelSparkModel LSSVMModel AbstractGridSearch BackPropagation ConjugateGradient GradBasedGlobalOptimizer ModelTuner AdaptiveHyperParameterMCMC
loglikelihood
Likelihood LikelihoodModel VectorIIDProbit VectorIIDSigmoid
logsig
TransferFunctions
low
MultivariateUniform
lower
CredibleInterval