Class Hierarchy

Go to the graphical class hierarchy

This inheritance list is sorted roughly, but not completely, alphabetically:
[detail level 123456]
 Cshark::AbstractBudgetMaintenanceStrategy< InputType >This is the abstract interface for any budget maintenance strategy
 Cshark::AbstractBudgetMaintenanceStrategy< RealVector >
 Cshark::AbstractConstraintHandler< SearchPointType >Implements the base class for constraint handling
 Cshark::AbstractConstraintHandler< Vector >
 Cshark::AbstractDistributionAbstract class for distributions
 Cshark::AbstractNearestNeighbors< InputType, LabelType >Interface for Nearest Neighbor queries
 Cshark::AbstractStoppingCriterion< ResultSetT >Base class for stopping criteria of optimization algorithms
 Cshark::AbstractStoppingCriterion< ResultSet >
 Cshark::AbstractStoppingCriterion< SingleObjectiveResultSet< PointType > >
 Cshark::AbstractStoppingCriterion< SingleObjectiveResultSet< RealVector > >
 Cshark::AbstractStoppingCriterion< ValidatedSingleObjectiveResultSet< PointType > >
 Cshark::AdditiveEpsilonIndicatorGiven a reference front R and an approximation F, calculates the additive approximation quality of F
 Cshark::BarsAndStripesGenerates the Bars-And-Stripes problem. In this problem, a 4x4 image has either rows or columns of the same value
 Cbase
 Cshark::BaseFastNonDominatedSort< Extractor >Implements the well-known non-dominated sorting algorithm
 Cshark::BaseRng< RNG >Collection of different variate generators for different distributions
 Cshark::statistics::BaseStatisticsObjectBase class for all Statistic Objects to be used with Statistics
 Cshark::BiasSolver< Matrix >
 Cshark::BiasSolverSimplex< Matrix >
 Cbidirectional_iterator_base
 Cshark::BinaryTree< InputT >Super class of binary space-partitioning trees
 Cshark::BinaryTree< Container::value_type >
 Cshark::BinaryTree< VectorType >
 Cshark::BitflipMutatorBitflip mutation operator
 Cshark::blas::Blocking< Matrix >Partitions the matrix in 4 blocks defined by one splitting point (i,j)
 Cshark::BlockMatrix2x2< Matrix >SVM regression matrix
 Cshark::BoundingBoxComputer< Set >Calculates bounding boxes
 Cshark::BoxConstrainedProblem< SVMProblem >Quadratic program with box constraints
 Cshark::BoxConstrainedProblem< Problem >
 Cshark::BoxedSVMProblem< MatrixT >Boxed problem for alpha in [lower,upper]^n and equality constraints
 Cshark::CachedMatrix< Matrix >Efficient quadratic matrix cache
 Cshark::CanBeCalled< Functor, Argument >Detects whether Functor(Argument) can be called
 Cshark::CMAChromosomeModels a CMAChromosomeof the elitist (MO-)CMA-ES that encodes strategy parameters
 Cshark::blas::const_expression< compressed_matrix< T, I > >
 Cshark::blas::const_expression< compressed_matrix< T, I > const >
 Cshark::blas::const_expression< compressed_vector< T, I > >
 Cshark::blas::const_expression< compressed_vector< T, I > const >
 Cshark::blas::const_expression< matrix< T, Orientation > >
 Cshark::blas::const_expression< matrix< T, Orientation > const >
 Cshark::blas::const_expression< triangular_matrix< T, Orientation, TriangularType > >
 Cshark::blas::const_expression< triangular_matrix< T, Orientation, TriangularType > const >
 Cshark::blas::const_expression< vector< T > >
 Cshark::blas::const_expression< vector< T > const >
 Cshark::ConstProxyReference< T >Sets the type of ProxxyReference
 Cshark::CSVMProblem< MatrixT >Problem formulation for binary C-SVM problems
 Cshark::CVFolds< DatasetTypeT >
 Cshark::CVFolds< DatasetType >
 Cshark::CVFolds< LabeledData< InputType, unsigned int > >
 Cshark::DataDistribution< InputType >A DataDistribution defines an unsupervised learning problem
 Cshark::DataDistribution< RealVector >
 Cshark::DataView< DatasetType >Constant time Element-Lookup for Datasets
 Cshark::DataView< const shark::LabeledData >
 Cshark::DataView< LabeledData< InputType, LabelType > const >
 Cshark::DataView< shark::Data< InputType > const >
 Cshark::DataView< shark::Data< LabelType > const >
 Cshark::DiffGeometric_distribution< IntType, RealType >Implements a diff geometric distribution
 Cshark::Dirichlet_distribution< RealType >Dirichlet distribution
 CDiscreteKernel
 Cshark::tags::DiscreteSpaceA Tag for EnumerationSpaces. It tells the Functions, that the space is discrete and can be enumerated
 Cshark::DistantModesCreates a set of pattern (each later representing a mode) which than are randomly perturbed to create the data set. The dataset was introduced in Desjardins et al. (2010) (Parallel Tempering for training restricted Boltzmann machines, AISTATS 2010)
 Cshark::DistTrainerContainerContainer for known distribution trainers
 Cshark::DivideTransformation function dividing the elements in a dataset by a scalar or component-wise by values stores in a vector
 Cshark::DoublePole
 Cshark::WilcoxonRankSumTest::ElementStores information about an observation
 Cshark::ElitistSelection< Extractor >Survival selection to find the next parent set
 Cshark::Energy< RBM >The Energy function determining the Gibbs distribution of an RBM
 Cshark::EnergyStoringTemperedMarkovChain< Operator >Implements parallel tempering but also stores additional statistics on the energy differences
 Cshark::QpSparseArray< QpFloatType >::EntryNon-default (non-zero) array entry
 Cshark::EPTournamentSelection< Extractor >Survival and mating selection to find the next parent set
 Cshark::Erlang_distribution< RealType >Implements an Erlang distribution
 Cshark::QpMcBoxDecomp< Matrix >::ExampleData structure describing one training example
 Cshark::QpMcSimplexDecomp< Matrix >::ExampleData structure describing one training example
 Cshark::ExampleModifiedKernelMatrix< InputType, CacheType >
 Cstd::exceptionSTL class
 Cshark::FFNetStructures
 Cshark::FitnessExtractor
 Cshark::Individual< PointType, FitnessTypeT, Chromosome >::FitnessOrderingOrdering relation by the fitness of the individuals(only single objective)
 Cshark::Gamma_distribution< RealType >Gamma distribution
 Cshark::GaussianKernelMatrix< T, CacheType >Efficient special case if the kernel is Gaussian and the inputs are sparse vectors
 Cshark::GeneralQuadraticProblem< MatrixT >Most gneral problem formualtion, needs to be configured by hand
 Cshark::GibbsOperator< RBMType >Implements Block Gibbs Sampling related transition operators for various temperatures
 Cshark::HMGSelectionCriterion
 Cshark::HyperGeometric_distribution< IntType, RealType >Hypergeometric distribution
 Cshark::HypervolumeApproximator< Rng >Implements an FPRAS for approximating the volume of a set of high-dimensional objects
 Cshark::HypervolumeCalculatorImplementation of the exact hypervolume calculation in m dimensions
 Cshark::HypervolumeIndicatorCalculates the hypervolume covered by a front of non-dominated points
 Cshark::IdentityFitnessExtractorFunctor that returns its argument without conversion
 Cshark::LeastContributorApproximator< Rng, ExactHypervolume >::IdentityFitnessExtractorReturns the supplied argument
 Cshark::ImageInformationStores name and size of image externally
 Cshark::INameableThis class is an interface for all objects which can have a name
 Cshark::IndicatorBasedSelection< Indicator >Implements the well-known indicator-based selection strategy
 Cshark::IndicatorBasedSelection< shark::HypervolumeIndicator >
 Cshark::Individual< PointType, FitnessTypeT, Chromosome >Individual is a simple templated class modelling an individual that acts as a candidate solution in an evolutionary algorithm
 Cshark::Individual< RealVector, double, CMAChromosome >
 Cshark::Individual< RealVector, FitnessType, CMAChromosome >
 Cshark::CrossEntropyMethod::INoiseTypeInterface class for noise type
 Cshark::InvertedGenerationalDistanceInverted generational distance for comparing Pareto-front approximations
 Cshark::IParameterizableTop level interface for everything that holds parameters
 Cshark::ISerializableAbstracts serializing functionality
 Cshark::IterativeNNQuery< DataContainer >Iterative nearest neighbors query
 Citerator_range
 Cshark::JaakkolaHeuristicJaakkola's heuristic and related quantities for Gaussian kernel selection
 Cshark::KernelMatrix< InputType, CacheType >Kernel Gram matrix
 Cshark::LabeledDataDistribution< InputType, LabelType >A LabeledDataDistribution defines a supervised learning problem
 Cshark::LabeledDataDistribution< InputType, unsigned int >
 Cshark::LabeledDataDistribution< RealVector, RealVector >
 Cshark::LabeledDataDistribution< RealVector, unsigned int >
 Cshark::LeastContributorApproximator< Rng, ExactHypervolume >Approximately determines the point of a set contributing the least hypervolume
 Cshark::LibSVMSelectionCriterion
 Cshark::LinearRankingSelection< Extractor >Implements a fitness-proportional selection scheme for mating selection that scales the fitness values linearly before carrying out the actual selection
 Cshark::LRUCache< T >Implements an LRU-Caching Strategy for arbitrary Cache-Lines
 Cshark::LRUCache< QpFloatType >
 Cshark::MarkovChain< Operator >A single Markov chain
 Cshark::blas::matrix_expression< E >Base class for Matrix Expression models
 Cshark::blas::matrix_expression< C >
 Cshark::blas::matrix_expression< dense_matrix_adaptor< T, Orientation > >
 Cshark::blas::matrix_expression< internal_transpose_proxy< M > >
 Cshark::blas::matrix_expression< matrix_addition< E1, E2 > >
 Cshark::blas::matrix_expression< matrix_binary< E1, E2, F > >
 Cshark::blas::matrix_expression< matrix_matrix_prod< MatA, MatB > >
 Cshark::blas::matrix_expression< matrix_range< M > >
 Cshark::blas::matrix_expression< matrix_range< Matrix > >
 Cshark::blas::matrix_expression< matrix_reference< M > >
 Cshark::blas::matrix_expression< matrix_scalar_multiply< E > >
 Cshark::blas::matrix_expression< matrix_transpose< M > >
 Cshark::blas::matrix_expression< matrix_unary< E, F > >
 Cshark::blas::matrix_expression< outer_product< E1, E2 > >
 Cshark::blas::matrix_expression< vector_repeater< V > >
 Cshark::blas::matrix_set_expression< E >Base class for expressions of matrix sets
 Cshark::blas::matrix_set_expression< matrix_set< element_type > >
 Cshark::blas::matrix_set_expression< matrix_set< RealMatrix > >
 Cshark::MaximumGainCriterionWorking set selection by maximization of the dual objective gain
 Cshark::MaximumGradientCriterionWorking set selection by maximization of the projected gradient
 Cshark::McPegasos< VectorType >Pegasos solver for linear multi-class support vector machines
 CMklKernelBase
 Cshark::MNISTReads in the famous MNIST data in possibly binarized form. The MNIST database itself is not included in Shark, this class just helps loading it
 Cshark::ModifiedKernelMatrix< InputType, CacheType >Modified Kernel Gram matrix
 Cshark::MultiNomialDistributionImplements a multinomial distribution
 Cshark::MultiplicativeEpsilonIndicatorGiven a reference front R and an approximation F, calculates the multiplicative approximation quality of F
 Cshark::MultiplyTransformation function multiplying the elements in a dataset by a scalar or component-wise by values stores in a vector
 Cshark::MultiVariateNormalDistributionImplements a multi-variate normal distribution with zero mean
 Cshark::MultiVariateNormalDistributionCholeskyMultivariate normal distribution with zero mean using a cholesky decomposition
 Cshark::MVPSelectionCriterion
 Cshark::detail::NeuronBase< DropoutNeuron< Neuron > >
 Cshark::detail::NeuronBase< FastSigmoidNeuron >
 Cshark::detail::NeuronBase< LinearNeuron >
 Cshark::detail::NeuronBase< LogisticNeuron >
 Cshark::detail::NeuronBase< RectifierNeuron >
 Cshark::detail::NeuronBase< TanhNeuron >
 Cshark::blas::noalias_proxy< C >
 Cnoncopyable
 Cshark::NormalTrainerTrainer for normal distribution
 Cshark::OnePointCrossoverImplements one-point crossover
 Cshark::PairRangeType< PairType, Range1, Range2 >
 Cshark::PairReference< Pair, Iterator1, Iterator2 >Given a type of pair and two iterators to zip together, returns the reference
 Cshark::ParetoDominanceComparator< Extractor >Implementation of the Pareto-Dominance relation under the assumption of all objectives to be minimized
 Cpartially_ordered
 Cshark::PartlyPrecomputedMatrix< Matrix >Partly Precomputed version of a matrix for quadratic programming
 Cshark::Pegasos< VectorType >Pegasos solver for linear (binary) support vector machines
 Cshark::PenalizingEvaluatorPenalizing evaluator for scalar objective functions
 Cshark::LeastContributorApproximator< Rng, ExactHypervolume >::Point< VectorType >Models a point and associated information for book-keeping purposes
 Cshark::EvaluationArchive< PointType, ResultT >::PointResultPairTypePair of point and result
 Cshark::PolynomialMutatorPolynomial mutation operator
 Cshark::PopulationBasedStepSizeAdaptationStep size adaptation based on the success of the new population compared to the old
 Cshark::PrecomputedMatrix< Matrix >Precomputed version of a matrix for quadratic programming
 Cshark::QpMcSimplexDecomp< Matrix >::PreferedSelectionStrategyWorking set selection eturning th S2DO working set
 Cshark::QpMcBoxDecomp< Matrix >::PreferedSelectionStrategyWorking set selection eturning th S2DO working set
 CProductKernel
 Cshark::QpBoxLinear< InputT >Quadratic program solver for box-constrained problems with linear kernel
 Cshark::QpBoxLinear< CompressedRealVector >
 Cshark::QpConfigSuper class of all support vector machine trainers
 Cshark::QpMcBoxDecomp< Matrix >
 Cshark::QpMcDecomp< Matrix >Quadratic program solver for multi class SVM problems
 Cshark::QpMcLinear< InputT >Generic solver skeleton for linear multi-class SVM problems
 Cshark::QpMcSimplexDecomp< Matrix >
 Cshark::QpSolutionPropertiesProperties of the solution of a quadratic program
 Cshark::QpSolver< Problem, SelectionStrategy >Quadratic program solver
 Cshark::QpSparseArray< QpFloatType >Specialized container class for multi-class SVM problems
 Cshark::QpStoppingConditionStopping conditions for quadratic programming
 Crandom_access_iterator_base
 Cshark::Individual< PointType, FitnessTypeT, Chromosome >::RankOrderingOrdering relation by the ranks of the individuals
 Cshark::RealSpaceThe RealSpace can't be enumerated. Infinite values are just too much
 Cshark::tags::RealSpaceA Tag for EnumerationSpaces. It tells the Functions, that the space is real and can't be enumerated
 Cshark::blas::compressed_vector< T, I >::reference
 Cshark::blas::compressed_matrix< T, I >::reference
 Cshark::RegularizedKernelMatrix< InputType, CacheType >Kernel Gram matrix with modified diagonal
 Cshark::WilcoxonRankSumTest::ResultStores result of Wilcoxon rank-sum test
 Cshark::RadiusMarginQuotient< InputType, CacheType >::Result
 Cshark::ResultSet< SearchPointT, ResultT >
 Cshark::ResultSet< SearchPointTypeT, double >
 Cshark::statistics::ResultTable< Parameter >Stores results of a running experiment
 Cshark::RFTrainer::RFAttribute
 Cshark::ROCROC-Curve - false negatives over false positives
 Cshark::RouletteWheelSelectionFitness-proportional selection operator
 Cshark::QpSparseArray< QpFloatType >::RowData structure describing a row of the sparse array
 Cshark::Sampler< Rng >Samples a random point
 Cshark::AbstractObjectiveFunction< PointType, ResultT >::SecondOrderDerivative
 CSHARK_ITERATOR_FACADE
 Cshark::ShiftTransformation function adding a vector or a scalar to the elements in a dataset
 Cshark::ShifterShifter problem
 Cshark::SimulatedBinaryCrossover< PointType >Simulated binary crossover operator
 Cshark::SimulatedBinaryCrossover< RealVector >
 Cshark::SinglePole
 Cshark::blas::SolveAXBFlag indicating that a system AX=B is to be solved
 Cshark::blas::SolveXABFlag indicating that a system XA=B is to be solved
 Cshark::QpBoxLinear< CompressedRealVector >::SparseVectorData structure for sparse vectors
 Cshark::CARTClassifier< LabelType >::SplitInfo
 Cshark::StateRepresents the State of an Object
 Cshark::statistics::Statistics< Parameter >Generates Statistics over the results of an experiment
 Cshark::detail::SubrangeKernelBase< InputType >
 Cshark::SvmProblem< Problem >
 Cshark::CARTTrainer::TableEntryTypes frequently used
 Cshark::WeightedSumKernel< InputType >::tBaseStructure describing a single m_base kernel
 Cshark::TemperedMarkovChain< Operator >
 Cshark::QpMcDecomp< Matrix >::tExampleData structure describing one training example
 Cshark::TimerTimer abstraction with microsecond resolution
 Cshark::TournamentSelection< Predicate >Tournament selection operator
 Cboost::serialization::tracking_level< shark::TypedFlags< T > >
 Cboost::serialization::tracking_level< std::vector< T > >
 Cshark::TransformedData< Functor, T >
 Cshark::TreeConstructionStopping criteria for tree construction
 Cshark::TruncateTransformation function truncating elements in a dataset
 Cshark::TruncateAndRescaleTransformation function first truncating and then rescaling elements in a dataset
 Cshark::TruncatedExponential_distribution< RealType >Boost random suitable distribution for an truncated exponential. See TruncatedExponential for more details
 Cshark::QpMcDecomp< Matrix >::tVariableData structure describing one variable of the problem
 Cshark::TwoPointStepSizeAdaptationStep size adaptation based on the success of the new population compared to the old
 Cshark::TwoStateSpace< State1, State2 >The TwoStateSpace is a discrete Space with only two values, for example {0,1} or {-1,1}
 Ctype
 Cshark::UniformCrossoverUniform crossover of arbitrary individuals
 Cshark::UniformRankingSelectionSelects individuals from the range of individual and offspring individuals
 Cshark::QpMcBoxDecomp< Matrix >::VariableData structure describing one m_variables of the problem
 Cshark::QpMcSimplexDecomp< Matrix >::VariableData structure describing one variable of the problem
 Cvariate_generator
 Cshark::blas::vector_expression< E >Base class for Vector Expression models
 Cshark::blas::vector_expression< C >
 Cshark::blas::vector_expression< dense_vector_adaptor< T > >
 Cshark::blas::vector_expression< matrix_column< M > >
 Cshark::blas::vector_expression< matrix_row< M > >
 Cshark::blas::vector_expression< matrix_row< Matrix > >
 Cshark::blas::vector_expression< matrix_vector_prod< MatA, VecV > >
 Cshark::blas::vector_expression< matrix_vector_range< M > >
 Cshark::blas::vector_expression< scalar_vector< T > >
 Cshark::blas::vector_expression< sparse_vector_adaptor< T, I > >
 Cshark::blas::vector_expression< vector_addition< E1, E2 > >
 Cshark::blas::vector_expression< vector_binary< E1, E2, F > >
 Cshark::blas::vector_expression< vector_range< V > >
 Cshark::blas::vector_expression< vector_reference< V > >
 Cshark::blas::vector_expression< vector_scalar_multiply< E > >
 Cshark::blas::vector_expression< vector_unary< E, F > >
 Cshark::blas::vector_set_expression< E >Base class for expressions of vector sets
 Cshark::VectorMatrixTraits< VectorType >Template which finds for every Vector type the best fitting Matrix
 Cshark::BoundingBoxComputer< Set >::VolumeComparatorCompares points based on their contributed volume
 Cshark::Weibull_distribution< RealType >Weibull distribution
 Cshark::WilcoxonRankSumTestWilcoxon rank-sum test / Mann–Whitney U test
 Cshark::WS2MaximumGradientCriterionWorking set selection by maximization of the projected gradient
 CP
 CTrainer