File List

Here is a list of all files with brief descriptions:

[detail level 1234567]

▼ examples
▼ ExampleProject
HelloWorld.cpp
▼ include
▼ shark
► Algorithms
► DirectSearch
► CMA
Chromosome.h
CMAIndividual.h
► Indicators
AdditiveEpsilonIndicator.h
HypervolumeIndicator.h
InvertedGenerationalDistance.h
LeastContributorApproximator.h
MultiplicativeEpsilonIndicator.h
► Operators
► Evaluation
PenalizingEvaluator.h
► Mutation
BitflipMutator.h
PolynomialMutation.h
► Recombination
OnePointCrossover.h
SimulatedBinaryCrossover.h
UniformCrossover.h
► Selection
ElitistSelection.h
EPTournamentSelection.h
IndicatorBasedSelection.h
LinearRanking.h
RouletteWheelSelection.h
TournamentSelection.h
UniformRanking.h
PopulationBasedStepSizeAdaptation.h
TwoPointStepSizeAdaptation.h
CMA.h
CMSA.h
CrossEntropyMethod.h
ElitistCMA.h
FastNonDominatedSort.h
FitnessExtractor.h
Grid.h
GridSearch.h
HypervolumeApproximator.h
HypervolumeCalculator.h
Individual.h
LMCMA.h
MOCMA.h
ParetoDominanceComparator.h
RealCodedNSGAII.h
SimplexDownhill.h
SMS-EMOA.h
SteadyStateMOCMA.h
VDCMA.h
► GradientDescent
AbstractLineSearchOptimizer.h
BFGS.h
CG.h
LBFGS.h
LineSearch.h
Rprop.h
SteepestDescent.h
TrustRegionNewton.h
► NearestNeighbors
AbstractNearestNeighbors.h
SimpleNearestNeighbors.h
TreeNearestNeighbors.h
► QP
BoxConstrainedProblems.h
QpBoxLinear.h
QpMcBoxDecomp.h
QpMcDecomp.h
QpMcLinear.h
QpMcSimplexDecomp.h
QpSolver.h
QpSparseArray.h
QuadraticProgram.h
SvmProblems.h
► StoppingCriteria
AbstractStoppingCriterion.h
GeneralizationLoss.h
GeneralizationQuotient.h
MaxIterations.h
TrainingError.h
TrainingProgress.h
ValidatedStoppingCriterion.h
► Trainers
► Budgeted
AbstractBudgetMaintenanceStrategy.h
KernelBudgetedSGDTrainer.h
MergeBudgetMaintenanceStrategy.h
ProjectBudgetMaintenanceStrategy.h
RemoveBudgetMaintenanceStrategy.h
► Distribution
DistTrainerContainer.h
GenericDistTrainer.h
NormalTrainer.h
AbstractSvmTrainer.h
AbstractTrainer.h
AbstractWeightedTrainer.h
CARTTrainer.h
CSvmTrainer.h
EpsilonSvmTrainer.h
FisherLDA.h
KernelMeanClassifier.h
KernelSGDTrainer.h
LassoRegression.h
LDA.h
LinearRegression.h
McReinforcedSvmTrainer.h
McSvmADMTrainer.h
McSvmATMTrainer.h
McSvmATSTrainer.h
McSvmCSTrainer.h
McSvmLLWTrainer.h
McSvmMMRTrainer.h
McSvmOVATrainer.h
McSvmWWTrainer.h
MissingFeatureSvmTrainer.h
NBClassifierTrainer.h
NormalizeComponentsUnitInterval.h
NormalizeComponentsUnitVariance.h
NormalizeComponentsWhitening.h
NormalizeComponentsZCA.h
NormalizeKernelUnitVariance.h
OneClassSvmTrainer.h
OptimizationTrainer.h
PCA.h
Perceptron.h
RegularizationNetworkTrainer.h
RFTrainer.h
SigmoidFit.h
AbstractMultiObjectiveOptimizer.h
AbstractOptimizer.h
AbstractSingleObjectiveOptimizer.h
JaakkolaHeuristic.h
KMeans.h
Pegasos.h
► Core
► Traits
ProxyReferenceTraits.h
► utility
CanBeCalled.h
functional.h
Iterators.h
KeyValuePair.h
Range.h
ScopedHandle.h
ZipPair.h
DLLSupport.h
Exception.h
Flags.h
INameable.h
IParameterizable.h
ISerializable.h
Math.h
OpenMP.h
ResultSets.h
State.h
Timer.h
► Data
BatchInterface.h
BatchInterfaceAdaptStruct.h
Csv.h
CVDatasetTools.h
DataDistribution.h
Dataset.h
DataView.h
ExportKernelMatrix.h
HDF5.h
LabelOrder.h
Libsvm.h
Pgm.h
SparseData.h
Statistics.h
WeightedDataset.h
► LinAlg
► BLAS
► kernels
► atlas
potrf.hpp
► cblas
cblas_inc.hpp
dot.hpp
gemm.hpp
gemv.hpp
tpmv.hpp
trmm.hpp
trmv.hpp
trsm.hpp
trsv.hpp
► default
dot.hpp
gemm.hpp
gemv.hpp
potrf.hpp
syev.hpp
tpmv.hpp
trmm.hpp
trmv.hpp
trsm.hpp
trsv.hpp
► lapack
fortran.hpp
syev.hpp
dot.hpp
gemm.hpp
gemv.hpp
matrix_assign.hpp
potrf.hpp
syev.hpp
tpmv.hpp
traits.hpp
trmm.hpp
trmv.hpp
trsm.hpp
trsv.hpp
vector_assign.hpp
assignment.hpp
blas.h
expression_types.hpp
fwd.hpp
io.hpp
lu.hpp
matrix.hpp
matrix_expression.hpp
matrix_proxy.hpp
matrix_set.hpp
matrix_sparse.hpp
operation.hpp
permutation.hpp
triangular_matrix.hpp
vector.hpp
vector_expression.hpp
vector_proxy.hpp
vector_sparse.hpp
Base.h
BlockMatrix2x2.h
CachedMatrix.h
Cholesky.h
eigenvalues.h
ExampleModifiedKernelMatrix.h
GaussianKernelMatrix.h
Initialize.h
KernelMatrix.h
LRUCache.h
Metrics.h
ModifiedKernelMatrix.h
PartlyPrecomputedMatrix.h
PrecomputedMatrix.h
RegularizedKernelMatrix.h
rotations.h
RQ.h
solveSystem.h
solveTriangular.h
svd.h
Tools.h
► Models
► Clustering
AbstractClustering.h
Centroids.h
ClusteringModel.h
HardClusteringModel.h
HierarchicalClustering.h
SoftClusteringModel.h
► Kernels
AbstractKernelFunction.h
AbstractMetric.h
ArdKernel.h
CSvmDerivative.h
DiscreteKernel.h
EvalSkipMissingFeatures.h
GaussianRbfKernel.h
KernelExpansion.h
KernelHelpers.h
LinearKernel.h
MissingFeaturesKernelExpansion.h
MklKernel.h
ModelKernel.h
MonomialKernel.h
MultiTaskKernel.h
NormalizedKernel.h
PolynomialKernel.h
ProductKernel.h
ScaledKernel.h
SubrangeKernel.h
WeightedSumKernel.h
► Trees
BinaryTree.h
CARTClassifier.h
KDTree.h
KHCTree.h
LCTree.h
RFClassifier.h
AbstractModel.h
Autoencoder.h
CMAC.h
ConcatenatedModel.h
Converter.h
ConvexCombination.h
FFNet.h
GaussianNoiseModel.h
ImpulseNoiseModel.h
LinearClassifier.h
LinearModel.h
LinearNorm.h
MeanModel.h
NBClassifier.h
NearestNeighborClassifier.h
NearestNeighborRegression.h
Neurons.h
Normalizer.h
OneVersusOneClassifier.h
OnlineRNNet.h
RBFLayer.h
RecurrentStructure.h
RNNet.h
SigmoidModel.h
Softmax.h
SoftNearestNeighborClassifier.h
TiedAutoencoder.h
► ObjectiveFunctions
► Benchmarks
► PoleSimulators
DoublePole.h
SinglePole.h
Ackley.h
Benchmarks.h
Cigar.h
CigarDiscus.h
CIGTAB1.h
CIGTAB2.h
ConstrainedSphere.h
DiffPowers.h
Discus.h
DTLZ1.h
DTLZ2.h
DTLZ3.h
DTLZ4.h
DTLZ5.h
DTLZ6.h
DTLZ7.h
ELLI1.h
ELLI2.h
Ellipsoid.h
Fonseca.h
GruauPole.h
GSP.h
Himmelblau.h
IHR1.h
IHR2.h
IHR3.h
IHR4.h
IHR6.h
LZ1.h
LZ2.h
LZ3.h
LZ4.h
LZ5.h
LZ6.h
LZ7.h
LZ8.h
LZ9.h
MarkovPole.h
NonMarkovPole.h
Rosenbrock.h
RotatedErrorFunction.h
Schwefel.h
Sphere.h
ZDT1.h
ZDT2.h
ZDT3.h
ZDT4.h
ZDT6.h
► Loss
AbsoluteLoss.h
AbstractLoss.h
CrossEntropy.h
CrossEntropyIndependent.h
DiscreteLoss.h
EpsilonHingeLoss.h
HingeLoss.h
HuberLoss.h
SquaredEpsilonHingeLoss.h
SquaredHingeLoss.h
SquaredLoss.h
TukeyBiweightLoss.h
ZeroOneLoss.h
AbstractConstraintHandler.h
AbstractCost.h
AbstractObjectiveFunction.h
BoxConstraintHandler.h
CombinedObjectiveFunction.h
CrossValidationError.h
ErrorFunction.h
EvaluationArchive.h
KernelBasisDistance.h
KernelTargetAlignment.h
LooError.h
LooErrorCSvm.h
NegativeAUC.h
NegativeGaussianProcessEvidence.h
NegativeLogLikelihood.h
NoisyErrorFunction.h
RadiusMarginQuotient.h
Regularizer.h
ROC.h
SparseAutoencoderError.h
SvmLogisticInterpretation.h
► Rng
AbstractDistribution.h
Bernoulli.h
Binomial.h
Cauchy.h
DiffGeometric.h
DiscreteUniform.h
Entropy.h
Erlang.h
Gamma.h
Geometric.h
GlobalRng.h
HyperGeometric.h
KullbackLeiberDivergence.h
LogNormal.h
NegExponential.h
Normal.h
Poisson.h
Rng.h
TruncatedExponential.h
Uniform.h
Weibull.h
► Statistics
► Distributions
MultiNomialDistribution.h
MultiVariateNormalDistribution.h
► Tests
WilcoxonRankSumTest.h
Statistics.h
► Unsupervised
► RBM
► GradientApproximations
ContrastiveDivergence.h
ExactGradient.h
MultiChainApproximator.h
SingleChainApproximator.h
► Neuronlayers
BinaryLayer.h
BipolarLayer.h
GaussianLayer.h
TruncatedExponentialLayer.h
► Problems
BarsAndStripes.h
DistantModes.h
MNIST.h
Shifter.h
► Sampling
EnergyStoringTemperedMarkovChain.h
GibbsOperator.h
MarkovChain.h
TemperedMarkovChain.h
► StateSpaces
RealSpace.h
TwoStateSpace.h
analytics.h
BinaryRBM.h
BipolarRBM.h
ConvolutionalBinaryRBM.h
ConvolutionalRBM.h
Energy.h
GaussianBinaryRBM.h
RBM.h
Tags.h
TruncExpBinaryRBM.h
▼ obj-x86_64-linux-gnu
▼ examples
► Data
Datasets.cpp
Normalization.cpp
Subsets.cpp
► EA
► MOO
AdditiveEpsilonIndicatorMain.cpp
MOCMAExperiment.cpp
MOCMASimple.cpp
► SOO
AckleyES.cpp
Archive.cpp
CMAExperiment.cpp
CMAPlot.cpp
CMASimple.cpp
ElitistCMASimple.cpp
TSP.cpp
► Statistics
Statistics.cpp
► Supervised
CARTTutorial.cpp
CSvmGridSearchTutorial.cpp
CSvmLinear.cpp
CSvmMaxLikelihoodMS.cpp
CSvmTutorial.cpp
CVFolds.cpp
DeepNetworkTraining.cpp
DeepNetworkTrainingRBM.cpp
elmTutorial.cpp
FFNNBasicTutorial.cpp
FFNNMultiClassCrossEntropy.cpp
KernelBudgetedSGDTutorial.cpp
KernelLogisticRegression.cpp
KernelRegression.cpp
KernelSelection.cpp
KNNCrossValidationTutorial.cpp
KNNTutorial.cpp
KTA-tutorial.cpp
LassoRegression.cpp
LDATutorial.cpp
linearRegressionTutorial.cpp
McSvm.cpp
McSvmLinear.cpp
MklKernelTutorial.cpp
MultiTaskSvm.cpp
OneVersusOne.cpp
quickstartTutorial.cpp
regressionTutorial.cpp
RFTutorial.cpp
StoppingCriteria.cpp
SubrangeKernelTutorial.cpp
VersatileClassificationTutorial-LDA.cpp
VersatileClassificationTutorial-Network.cpp
VersatileClassificationTutorial-NN.cpp
VersatileClassificationTutorial-RF.cpp
VersatileClassificationTutorial-SVM.cpp
► Unsupervised
AutoEncoderTutorial.cpp
BinaryRBM.cpp
DenoisingAutoencoderTutorial.cpp
HierarchicalClustering.cpp
KMeansTutorial.cpp
MaxLogLikelihood.cpp
OneClassSvm.cpp
PCA.cpp
PCATutorial.cpp
SparseAETutorial.cpp