Here is a list of all class members with links to the classes they belong to:
- l -
- label
: shark::CARTClassifier< LabelType >::SplitInfo
, shark::LassoRegression< InputVectorType >
, shark::QpMcBoxDecomp< Matrix >
, shark::QpMcSimplexDecomp< Matrix >
- LabelContainer
: shark::LabeledData< InputT, LabelT >
- LabeledData
: shark::Data< Type >
, shark::LabeledData< InputT, LabelT >
- LabelOrder()
: shark::LabelOrder
- labels()
: shark::LabeledData< InputT, LabelT >
, shark::WeightedLabeledData< InputT, LabelT >
- LabelType
: shark::AbstractCost< LabelT, OutputT >
, shark::AbstractLoss< LabelT, OutputT >
, shark::AbstractTrainer< Model, LabelTypeT >
, shark::AbstractWeightedTrainer< Model, LabelTypeT >
, shark::CrossValidationError< ModelTypeT, LabelTypeT >
, shark::LabeledData< InputT, LabelT >
, shark::OptimizationTrainer< Model, LabelTypeT >
, shark::WeightedLabeledData< InputT, LabelT >
- lambda()
: shark::CMA
, shark::CMSA
, shark::LassoRegression< InputVectorType >
, shark::LMCMA
, shark::TruncatedExponential< RngType >
, shark::TruncatedExponential_distribution< RealType >
, shark::VDCMA
- LassoRegression()
: shark::LassoRegression< InputVectorType >
- lastLap()
: shark::Timer
- layerMatrices()
: shark::FFNet< HiddenNeuron, OutputNeuron >
- layerMatrix()
: shark::FFNet< HiddenNeuron, OutputNeuron >
- LBFGS()
: shark::LBFGS
- LCTree()
: shark::LCTree< VectorType, CuttingAccuracy >
- LDA()
: shark::LDA
- learningRate()
: shark::PopulationBasedStepSizeAdaptation
, shark::SteepestDescent
- leastContributor()
: shark::AdditiveEpsilonIndicator
, shark::HypervolumeIndicator
, shark::InvertedGenerationalDistance
, shark::LeastContributorApproximator< Rng, ExactHypervolume >
, shark::MultiplicativeEpsilonIndicator
- LeastContributorApproximator()
: shark::LeastContributorApproximator< Rng, ExactHypervolume >
- left()
: shark::BinaryTree< InputT >
, shark::blas::SolveAXB
, shark::blas::SolveXAB
- leftNodeId
: shark::CARTClassifier< LabelType >::SplitInfo
- lg()
: shark::Pegasos< VectorType >
- lhs()
: shark::blas::outer_product< E1, E2 >
- line()
: shark::Exception
- linear()
: shark::BoxConstrainedProblem< SVMProblem >
, shark::BoxedSVMProblem< MatrixT >
- LINEAR
: shark::CMA
- linear
: shark::CSVMProblem< MatrixT >
, shark::GeneralQuadraticProblem< MatrixT >
, shark::QpMcDecomp< Matrix >
- Linear
: shark::RecurrentStructure
- linear()
: shark::SvmProblem< Problem >
- LinearClassifier()
: shark::LinearClassifier< VectorType >
- LinearCSvmTrainer()
: shark::LinearCSvmTrainer< InputType >
- LinearKernel()
: shark::LinearKernel< InputType >
- LinearMcSvmADMTrainer()
: shark::LinearMcSvmADMTrainer< InputType >
- LinearMcSvmATMTrainer()
: shark::LinearMcSvmATMTrainer< InputType >
- LinearMcSvmATSTrainer()
: shark::LinearMcSvmATSTrainer< InputType >
- LinearMcSvmCSTrainer()
: shark::LinearMcSvmCSTrainer< InputType >
- LinearMcSvmLLWTrainer()
: shark::LinearMcSvmLLWTrainer< InputType >
- LinearMcSvmMMRTrainer()
: shark::LinearMcSvmMMRTrainer< InputType >
- LinearMcSvmOVATrainer()
: shark::LinearMcSvmOVATrainer< InputType >
- LinearMcSvmReinforcedTrainer()
: shark::LinearMcSvmReinforcedTrainer< InputType >
- LinearMcSvmWWTrainer()
: shark::LinearMcSvmWWTrainer< InputType >
- LinearModel()
: shark::LinearModel< InputType >
- LinearNoise()
: shark::CrossEntropyMethod::LinearNoise
- LinearNorm()
: shark::LinearNorm
- LinearRankingSelection()
: shark::LinearRankingSelection< Extractor >
- LinearRegression()
: shark::LinearRegression
- lineLength()
: shark::LRUCache< T >
- lineSearch()
: shark::AbstractLineSearchOptimizer
- LineSearch()
: shark::LineSearch
- lineSearchType()
: shark::LineSearch
- LineSearchType
: shark::LineSearch
- listIndex()
: shark::LRUCache< T >
- LMCMA()
: shark::LMCMA
- load()
: shark::ISerializable
- location()
: shark::LogNormal< RngType >
- Logistic
: shark::RecurrentStructure
- logMarginalize()
: shark::BinaryLayer
, shark::BipolarLayer
, shark::GaussianLayer
, shark::TruncatedExponentialLayer
- logNormal()
: shark::BaseRng< RNG >
- LogNormal()
: shark::LogNormal< RngType >
- logP()
: shark::AbstractDistribution
, shark::Normal< RngType >
- logProbability()
: shark::BinaryLayer
, shark::BipolarLayer
, shark::GaussianLayer
- logUnnormalizedProbabilityHidden()
: shark::Energy< RBM >
- logUnnormalizedProbabilityVisible()
: shark::Energy< RBM >
- LooError()
: shark::LooError< ModelTypeT, LabelType >
- LooErrorCSvm()
: shark::LooErrorCSvm< InputType, CacheType >
- lossGradientADM()
: shark::McPegasos< VectorType >
- lossGradientADS()
: shark::McPegasos< VectorType >
- lossGradientANH()
: shark::McPegasos< VectorType >
- lossGradientATM()
: shark::McPegasos< VectorType >
- lossGradientATS()
: shark::McPegasos< VectorType >
- LossGradientFunction
: shark::McPegasos< VectorType >
- lossGradientRDM()
: shark::McPegasos< VectorType >
- lossGradientRDS()
: shark::McPegasos< VectorType >
- LossType
: shark::KernelBudgetedSGDTrainer< InputType, CacheType >
, shark::KernelSGDTrainer< InputType, CacheType >
, shark::LooError< ModelTypeT, LabelType >
, shark::OptimizationTrainer< Model, LabelTypeT >
- low()
: shark::DiscreteUniform< RngType >
, shark::Uniform< RngType >
- lower()
: shark::BoxConstraintHandler< Vector >
, shark::KDTree< InputT >
- lowerBound()
: shark::CMA
- lowerCholeskyFactor()
: shark::MultiVariateNormalDistributionCholesky
- lowerLeft()
: shark::blas::Blocking< Matrix >
- LowerQuantile()
: shark::statistics::LowerQuantile
- lowerRight()
: shark::blas::Blocking< Matrix >
- LRUCache()
: shark::LRUCache< T >
- LZ1()
: shark::LZ1
- LZ2()
: shark::LZ2
- LZ3()
: shark::LZ3
- LZ4()
: shark::LZ4
- LZ5()
: shark::LZ5
- LZ6()
: shark::LZ6
- LZ7()
: shark::LZ7
- LZ8()
: shark::LZ8
- LZ9()
: shark::LZ9