sgpp::datadriven Namespace Reference

Namespaces
namespace	clusteringmpi
namespace	ClusteringOCL
namespace	DBMatOfflineFactory
	factories to build the specialization of the DBMatOffline objects.
namespace	DBMatOnlineDEFactory
namespace	DensityOCLMultiPlatform
namespace	MultipleEvalHPX
namespace	PermutationUtil
namespace	PiecewiseConstantRegression
namespace	streamingBSplineOCL
namespace	StreamingModOCLFastMultiPlatform
namespace	StreamingModOCLMaskMultiPlatform
namespace	StreamingModOCLOpt
namespace	StreamingModOCLUnified
namespace	StreamingOCLMultiPlatform
namespace	x86simple

Classes
class	AbstractOperationMultipleEvalSubspace
class	Accuracy
	Metric that quantifies the difference between predicted values and actual values in terms of mean squared error (MSE). More...
class	AlgorithmAdaBoostBase
class	AlgorithmAdaBoostIdentity
class	AlgorithmMultipleEvaluationDistributed
	Abstract implementation for distributed multiple function evaluations. More...
class	ArffFileSampleProvider
	ArffFileSampleProvider allows reading data in ARFF format into a sgpp::datadriven::Dataset object. More...
class	ARFFTools
	Class that provides functionality to read ARFF files. More...
struct	AssignBatchNetworkMessage
	Message wrapped in MPI_Packet specifying an order to a worker to train from a batch. More...
struct	AssignSystemMatrixUpdateNetworkMessage
	Message wrapped in MPI_Packet specifying an order to a worker to update a class' system matrix decomposition. More...
struct	AssignTaskResult
	Used by the MPI Task Scheduler to deliver the result of assigning the requested task. More...
class	BayesianOptimization
	Class to host all methods to perform Bayesian Optimization. More...
class	BlacsProcessGrid
	This class represents a BLACS process grid for use with ScaLAPACK. More...
class	BOConfig
	Container class to store a conrete hyperparameter configuration for interaction with Bayesian Optimization. More...
class	BoHyperparameterOptimizer
	BoHyperparameterOptimizer coordinates data input, fitting and validation modules similarly to SparseGridMiner. More...
class	ClassificationFitterFactory
	Concrete factory to build instances of sgpp::datadriven::ModelFittingClassification. More...
class	ClassificationLearner
	The ClassificationLearner class Solves a classification problem. More...
class	ClassificationMinerFactory
	Concrete Factory that builds an instance of sgpp::datadriven::SparseGridMiner for classification. More...
class	ClassificationRefinementFunctor
	Classification refinement builds up the combined grid of all classes, then iterates through it always keeping track of the neighbors to detect class changes between neighbors. More...
struct	ClassificatorQuality
	struct to encapsulate the classsifiers quality by its characteristic numbers More...
class	CombiScheme
class	ConfigurationBit
	This class implements a boolean representation of hyperparameters for harmonica. More...
class	ConfigurationRestriction
	This class represents a constraint on the ConfigurationBits used by harmonica. More...
class	ContinuousParameter
	Concrete class for hyperparameter with continuous values. More...
struct	CrossvalidationConfiguration
struct	CrossvalidationForRegularizationConfiguration
class	CSVFileSampleProvider
	CSVFileSampleProvider allows reading data in CSV format into a sgpp::datadriven::Dataset object. More...
class	CSVTools
	Class that provides functionality to read CSV files. More...
class	CSVWriter
	Class that provides functionality to write a Dataset to a CSV file. More...
struct	DatabaseConfiguration
	Configuration structure for the offline datamatrix decomposition database. More...
class	DataBasedRefinementFunctor
	Data based refinement uses data points to find refinement candidates. More...
class	DataMatrixDistributed
	Class to represent a DataMatrix which is distributed on a process grid. More...
class	DataMiningConfigParser
class	Dataset
class	DatasetGenerator
class	DatasetTools
class	DataShufflingFunctor
	A class to provide functionality to shuffle (reorder) the data samples before the sample provider accesses it. More...
class	DataShufflingFunctorCrossValidation
	A pseudo shuffling functor, that maps indices 0...foldSize-1 to the current fold while mapping the other indices sequentially to the rest of the dataset. More...
class	DataShufflingFunctorFactory
	Concrete factory to build an instance of sgpp::datadriven::DataShufflingFunctor. More...
class	DataShufflingFunctorRandom
	A simple shuffling functor for data samples that performs a random shuffling of the data. More...
class	DataShufflingFunctorSequential
	A simple shuffling functor for data samples that performs no shuffling at all, i.e. More...
class	DataSource
	DataSource is a high level, easy to use interface for accessing data provided by a all kinds of sgpp::datadriven::SampleProvider. More...
class	DataSourceBuilder
	Generate an instance of sgpp::datadriven::DataSource using the Builder Pattern. More...
struct	DataSourceConfig
	Configuration structure used for all kinds of SampleProviders including default values. More...
class	DataSourceCrossValidation
	DataSourceCrossValidation is a high level interface to provide functionality for processing data using a cross validation enviroment. More...
class	DataSourceFileTypeParser
	Convenience class to convert strings to sgpp::datadriven::DataSourceFileType and generate string representations for values of sgpp::datadriven::DataSourceFileType. More...
class	DataSourceIterator
	Iterator object for walking convenient walking over the batches of a sgpp::datadriven::DataSource. More...
class	DataSourceShufflingTypeParser
	Convenience class to convert strings to sgpp::datadriven::DataSourceShufflingType and generate string representations for values of sgpp::datadriven::DataSourceShufflingType. More...
class	DataSourceSplitting
	DataSourceSlitting is a high level interface to provide functionality for processing data epoch-wise with a validation set that is retrieved at initialization time using the first samples the sample provider provides. More...
class	DataTransformation
	DataTransformation is an abstraction for an object that provides different transformations on datasets, for example Rosenblatt-transformation to get a uniform distribution over the unit cube. More...
class	DataTransformationBuilder
	Helper class to build all kinds of transformation based on given configuration. More...
struct	DataTransformationConfig
class	DataTransformationTypeParser
	Convenience class to convert strings to sgpp::datadriven::DataTransformationType and generate string representations for values of sgpp::datadriven::DataTransformationType. More...
class	DataVectorDistributed
class	DBMatDatabase
	A database class to store and retrieve online matrix decompositions for the sparse grid density estimation. More...
class	DBMatDecompMatrixSolver
class	DBMatDMS_SMW
	This class solves an (lhs + lambda*I) * alpha = b system of linear equations after the offline and online phases are done. More...
class	DBMatDMSChol
	Class to solve the system of equations with a LL'-decomposed matrix. More...
class	DBMatDMSDenseIChol
	Solve the system of equations with a LL'-decomposed matrix where LL' is created by an iterative, incomplete cholesky factorization on a dense matrix. More...
class	DBMatDMSOrthoAdapt
	This class solves an (lhs + lambda*I) * alpha = b system of linear equations after the offline and online phases are done. More...
class	DBMatObjectStore
class	DBMatOffline
	Class that is used to decompose and store the left-hand-side matrix for the density based classification approach (The classification is divided into two parts: the offline step that does not depend on the actual data and the online step that depends on the data). More...
class	DBMatOfflineChol
	DBMatOffline specialization that uses a cholesky factorization on a dense matrix. More...
class	DBMatOfflineDenseIChol
	DBMatOfflineChol specialization that uses a parallel, iterative incomplete cholesky factorization on a dense matrix. More...
class	DBMatOfflineGE
	DBMatOffline specialization as a base class for all algorithms based on gaussian elimination on a dense matrix. More...
class	DBMatOfflineOrthoAdapt
class	DBMatOfflinePermutable
class	DBMatOnline
	Class for objects that can be used in the online step of the classification (The classification is divided into two parts: the offline step that does not depend on the actual data and the online step that depends on the data) More...
class	DBMatOnlineDE
	Class that stores, generates and manipulates a density function during online phase in on/off learning. More...
class	DBMatOnlineDE_SMW
class	DBMatOnlineDEChol
class	DBMatOnlineDEOrthoAdapt
class	DBMatPermutationFactory
class	DensityDifferenceEstimationMinerFactory
	Concrete Factory that builds an instance of sgpp::datadriven::SparseGridMiner for Density Difference Estimation. More...
class	DensityDifferenceSystemMatrix
	Class that implements the virtual class OperationMatrix for the application of density estimation for the Systemmatrix by using a density difference function for two input datasets. More...
struct	DensityEstimationConfiguration
class	DensityEstimationFitterFactory
	Concrete factory to build instances of sgpp::datadriven::ModelFittingDensityEstimation. More...
class	DensityEstimationMinerFactory
	Concrete Factory that builds an instance of sgpp::datadriven::SparseGridMiner for Density Estimation. More...
class	DensityEstimationTypeParser
class	DensityEstimator
class	DensityRatioEstimationMinerFactory
	Concrete Factory that builds an instance of sgpp::datadriven::SparseGridMiner for Density Ratio Estimation. More...
class	DensitySystemMatrix
	Class that implements the virtual class OperationMatrix for the application of classification for the Systemmatrix by using a density function. More...
class	DiscreteParameter
	concrete class for hyperparameter with discrete values More...
class	DMConfigTools
class	DMSystemMatrix
	Class that implements the virtual class base::OperationMatrix for applications for the Systemmatrix. More...
class	DMSystemMatrixBase
	Abstract class that defines the virtual class base::OperationMatrix for classification and regression problems. More...
class	DMSystemMatrixBaseSP
	Abstract class that defines the virtual class base::OperationMatrix for classification and regression problems (single precision version) More...
class	DMSystemMatrixDRE
	Abstract class that defines the virtual class base::OperationMatrix for the density ratio estimation problem. More...
class	DMWeightMatrix
	Class that implements the virtual class OperationMatrix for the application of classification for the Systemmatrix with weight. More...
class	EpanechnikovKernel
class	FileSampleDecorator
	FileSampleDecorator provides an interface to provide generic manipulations for various kinds of sgpp::datadriven::FileSampleProvider using the decorator pattern. More...
class	FileSampleProvider
	sgpp::datadriven::FileSampleProvider is an specialization of sgpp::datadriven::SampleProvider and provides an interface for all sample providers that get their samples from files. More...
class	FitterConfiguration
	General configuration object for fitters. More...
class	FitterConfigurationClassification
	Configuration for fitter scenarios using classification. More...
class	FitterConfigurationDensityEstimation
	Configuration for fitter scenarios using density estimation. More...
class	FitterConfigurationLeastSquares
	Configuration for fitter scenarios using least squares optimization. More...
class	FitterFactory
	Abstract factory to build all kinds of fitters/models based on a given configuration. More...
class	FitterTypeParser
	Convenience class to convert strings to sgpp::datadriven::FitterType and generate string representations for values of sgpp::datadriven::FitterType. More...
class	Friedman1Generator
class	Friedman2Generator
class	Friedman3Generator
class	GaussianKernel
struct	GeometryConfiguration
class	GeometryConfigurationParser
class	GridFactory
	Factory class to create grids based on a configuration file. More...
class	GridPointBasedRefinementFunctor
	Grid Point based refinement for classification problems solved by a SG density estimation approach. More...
class	Harmonica
	Class to host all methods required to perform the harmonica algorithm. More...
class	HarmonicaHyperparameterOptimizer
	HarmonicaHyperparameterOptimizer coordinates data input, fitting and validation modules similarly to SparseGridMiner. More...
struct	HashGridPointCompare
class	HPOConfig
	Configuration for HyperparameterOptimizer. More...
class	HyperParameter
	Class to represent a hyperparameter. More...
class	HyperparameterOptimizer
	HyperparameterOptimizer uses fitters provided by a fitterFactory to test in a SparseGridMiner It offers access to different hyperparameter optimization procedures. More...
class	KDEMaximumLikelihoodCrossValidation
class	Kernel
class	KernelDensityEstimator
class	Learner
	This class implements standard sparse grid regression with an arbitrary regularization operator. More...
class	LearnerBase
	Abstract class that implements a regression/classification learner based on spatial adaptive Sparse Grids. More...
class	LearnerBaseSP
	Abstract class that implements a regression/classification learner based on spatial adaptive Sparse Grids. More...
struct	LearnerConfiguration
	Structure that contains information about the learners behaviour. More...
class	LearnerLeastSquaresIdentity
	This class implements standard sparse grid regression with an Identity matrix as regularization operator. More...
class	LearnerScenario
class	LearnerSGD
	LearnerSGD learns the data using stochastic gradient descent. More...
class	LearnerSGDE
class	LearnerSGDEConfiguration
class	LearnerSGDEOnOffParallel
	LearnerSGDEOnOffParallel learns the data using sparse grid density estimation. More...
class	LearnerSVM
	LearnerSVM learns the data using support vector machines and sparse grid kernels. More...
struct	LearnerTiming
	strcut to encapsulate the learner's timings during training More...
struct	LearnerVectorizedPerformance
	struct that defines return for calculation the performance of a vectorized learner More...
class	LearnerVectorizedPerformanceCalculator
	Class that provides functionality in order to determine a LearnerVectorized's performance. More...
class	LeastSquaresRegressionFitterFactory
	Concrete factory to build instances of sgpp::datadriven::ModelFittingLeastSquares. More...
class	LeastSquaresRegressionMinerFactory
	Concrete Factory that builds an instance of sgpp::datadriven::SparseGridMiner for Least Squares Regression. More...
struct	LevelIndexPair
	Pair to hold the level and the index of a grid point in one dimension. More...
class	LogDensitySystemMatrix
	Class that implements the virtual class OperationMatrix for the application of classification for the Systemmatrix by using a density function. More...
struct	MakePositiveConfiguration
class	MatrixDecompositionTypeParser
class	MaximumLikelihoodCrossValidation
struct	MergeGridNetworkMessage
	Packet wrapper in MPI_Packet containing segmented data from the alpha vector of the trained system. More...
struct	MessageTrackRequest
	Structure that holds data for pending tracking requests that need to be checked against incoming messages. More...
class	MetaLearner
class	Metric
	We use metrics to quantify approximation quality of a trained model. More...
class	MinerFactory
	Abstract factory to build different kinds of Miners based on a configuration which is parsed from a file. More...
class	ModelFittingBase
	Base class for arbitrary machine learning models based on adaptive sparse grids. More...
class	ModelFittingBaseSingleGrid
	Base class for models operating on a single grid (i.e. More...
class	ModelFittingClassification
	Fitter object that encapsulates density based classification using instances of ModelFittingDensityEstimation for each class. More...
class	ModelFittingDensityDifferenceEstimationCG
	Fitter object that encapsulates the usage of sparse grid density difference estimation with identity as regularization. More...
class	ModelFittingDensityDifferenceEstimationOnOff
	Fitter object that encapsulates the usage of sparse grid density difference estimation with identity as regularization. More...
class	ModelFittingDensityEstimation
	Abstract super class to encapsulate density estimation models such as using offline/-online splitting or conjugate gradients in order to solve the system. More...
class	ModelFittingDensityEstimationCG
	Fitter object that encapsulates the usage of sparse grid density estimation with identity as regularization. More...
class	ModelFittingDensityEstimationCombi
	Abstract super class to encapsulate density estimation models working with multiple Grids. More...
class	ModelFittingDensityEstimationOnOff
	Fitter object that encapsulates the usage of sparse grid density estimation with identity as regularization. More...
class	ModelFittingDensityEstimationOnOffParallel
	Fitter object that encapsulates the usage of sparse grid density estimation with identity as regularization. More...
class	ModelFittingDensityRatioEstimation
	Fitter object that encapsulates the usage of sparse grid based density ratio estimation, based on the regression model with identity as regularization. More...
class	ModelFittingLeastSquares
	Fitter object that encapsulates the usage of sparse grid based regression with identity as regularization. More...
class	MortonOrder
struct	MPI_Packet
	A packet sent over MPI, using a command as a descriptor, and a wrapped package in the payload for data. More...
class	MPIMethods
class	MPIRequestPool
class	MPITaskScheduler
class	MSE
	Metric that quantifies the difference between predicted values and actual values in terms of mean squared error (MSE). More...
class	MultiGridRefinementFunctor
	Abstract super-class for refinement functors operating on multiple grids. More...
class	MultipleClassRefinementFunctor
	Multiple class refinement is based on the zero-crossing based refinement. More...
class	MultiSurplusRefinementFunctor
	Wrapper of SurplusRefinementFunctor for multi grid scenarios. More...
class	NearestNeighbors
	The NearestNeighbors class. More...
class	NegativeLogLikelihood
	Metric that quantifies the likelihood of a dataset given the density function. More...
class	OperationCovariance
	This class provides the covariance matrix a sparse grid function. More...
class	OperationDensityConditional
	Conditionalize Probability Density Function. More...
class	OperationDensityConditionalKDE
class	OperationDensityConditionalLinear
	Marginalize Probability Density Function. More...
class	OperationDensityMarginalize
	Marginalize Probability Density Function. More...
class	OperationDensityMarginalizeKDE
	Marginalize Probability Density Function. More...
class	OperationDensityMarginalizeLinear
	Marginalize Probability Density Function. More...
class	OperationDensityMargTo1D
	Marginalize Probability Density Function. More...
class	OperationDensityRejectionSampling
	Sampling on all dimensions. More...
class	OperationDensityRejectionSamplingLinear
	Sampling with rejection sampling method. More...
class	OperationDensitySampling
	Sampling on all dimensions. More...
class	OperationDensitySampling1D
	Sample 1D Probability Density Function. More...
class	OperationDensitySampling1DLinear
class	OperationDensitySamplingLinear
	keep applying marginalize to function until it's reduced to only 1 dimension More...
class	OperationDotProductLinear
class	OperationDotProductModLinear
class	OperationInverseRosenblattTransformation
	Sampling on all dimensions. More...
class	OperationInverseRosenblattTransformation1DBspline
class	OperationInverseRosenblattTransformation1DBsplineBoundary
class	OperationInverseRosenblattTransformation1DBsplineClenshawCurtis
class	OperationInverseRosenblattTransformation1DLinear
class	OperationInverseRosenblattTransformation1DModBspline
class	OperationInverseRosenblattTransformation1DModBsplineClenshawCurtis
class	OperationInverseRosenblattTransformation1DModPoly
class	OperationInverseRosenblattTransformation1DModPolyClenshawCurtis
class	OperationInverseRosenblattTransformation1DPoly
class	OperationInverseRosenblattTransformation1DPolyBoundary
class	OperationInverseRosenblattTransformation1DPolyClenshawCurtis
class	OperationInverseRosenblattTransformation1DPolyClenshawCurtisBoundary
class	OperationInverseRosenblattTransformationBspline
	keep applying marginalize to function until it's reduced to only 1 dimension More...
class	OperationInverseRosenblattTransformationBsplineBoundary
	keep applying marginalize to function until it's reduced to only 1 dimension More...
class	OperationInverseRosenblattTransformationBsplineClenshawCurtis
	keep applying marginalize to function until it's reduced to only 1 dimension More...
class	OperationInverseRosenblattTransformationKDE
	Do inverse transformation in all dimensions. More...
class	OperationInverseRosenblattTransformationLinear
	keep applying marginalize to function until it's reduced to only 1 dimension More...
class	OperationInverseRosenblattTransformationModBspline
	keep applying marginalize to function until it's reduced to only 1 dimension More...
class	OperationInverseRosenblattTransformationModBsplineClenshawCurtis
	keep applying marginalize to function until it's reduced to only 1 dimension More...
class	OperationInverseRosenblattTransformationModPoly
	keep applying marginalize to function until it's reduced to only 1 dimension More...
class	OperationInverseRosenblattTransformationModPolyClenshawCurtis
	keep applying marginalize to function until it's reduced to only 1 dimension More...
class	OperationInverseRosenblattTransformationPoly
	keep applying marginalize to function until it's reduced to only 1 dimension More...
class	OperationInverseRosenblattTransformationPolyBoundary
	keep applying marginalize to function until it's reduced to only 1 dimension More...
class	OperationInverseRosenblattTransformationPolyClenshawCurtis
	keep applying marginalize to function until it's reduced to only 1 dimension More...
class	OperationInverseRosenblattTransformationPolyClenshawCurtisBoundary
	keep applying marginalize to function until it's reduced to only 1 dimension More...
class	OperationLimitFunctionValueRange
class	OperationMakePositive
	This class enforces the function value range of a sparse grid function to be larger than 0. More...
class	OperationMakePositiveCandidateSetAlgorithm
class	OperationMakePositiveFindIntersectionCandidates
class	OperationMakePositiveFindIntersectionCandidatesJoin
class	OperationMakePositiveHybridFindIntersectionCandidates
class	OperationMakePositiveInterpolateBoundaryOfSupport
class	OperationMakePositiveInterpolateExp
class	OperationMakePositiveInterpolateFunction
class	OperationMakePositiveInterpolationAlgorithm
class	OperationMakePositiveLoadFullGridCandidates
class	OperationMakePositiveSetToZero
class	OperationMultiEvalCuda
	OperationMultipleEval for polynomial basis functions (grad >= 2) using CUDA on grids without boundary nodes. More...
class	OperationMultiEvalHPX
	This class is a HPX wrapper for other MultiEval-operations that uses a very simple master-slave distributed processing. More...
class	OperationMultiEvalModMaskStreaming
class	OperationMultiEvalMPI
	This class is a MPI wrapper for other MultiEval-operations that uses a very simple master-slave MPI parallelization. More...
class	OperationMultiEvalStreaming
class	OperationMultiEvalStreamingBSpline
class	OperationMultiEvalStreamingBSplineOCL
class	OperationMultiEvalStreamingModOCLFastMultiPlatform
class	OperationMultiEvalStreamingModOCLMaskMultiPlatform
class	OperationMultiEvalStreamingModOCLOpt
class	OperationMultiEvalStreamingModOCLUnified
class	OperationMultipleEvalConfiguration
class	OperationMultipleEvalDistributed
	Distributed interface for OperationMultipleEval. More...
class	OperationMultipleEvalLinearDistributed
	This class is a distributed version of sgpp::base::OperationMultipleEvalLinear, it uses ScaLAPACK. More...
class	OperationMultipleEvalMatrix
	wrapper class for matrix multiplication for use in solver More...
class	OperationMultipleEvalModLinearDistributed
	This class is a distributed version of sgpp::base::OperationMultipleEvalModLinear, it uses ScaLAPACK. More...
class	OperationMultipleEvalSubspaceCombined
	Multiple evaluation operation that uses the subspace structure to save work compared to the naive or streaming variants. More...
class	OperationMultipleEvalSubspaceSimple
	Multiple evaluation operation that uses the subspace structure to save work compared to the naive or streaming variants. More...
class	OperationPiecewiseConstantRegression
class	OperationRegularizationDiagonal
	Implementation of the application of a diagonal matrix to a DataVector for regularization. More...
class	OperationRegularizationDiagonalLinearBoundary
	Implementation of the application of a diagonal matrix to a DataVector for regularization. More...
class	OperationRosenblattTransformation
	Sampling on all dimensions. More...
class	OperationRosenblattTransformation1DBspline
class	OperationRosenblattTransformation1DBsplineBoundary
class	OperationRosenblattTransformation1DBsplineClenshawCurtis
class	OperationRosenblattTransformation1DLinear
class	OperationRosenblattTransformation1DModBspline
class	OperationRosenblattTransformation1DModBsplineClenshawCurtis
class	OperationRosenblattTransformation1DModPoly
class	OperationRosenblattTransformation1DModPolyClenshawCurtis
class	OperationRosenblattTransformation1DPoly
class	OperationRosenblattTransformation1DPolyBoundary
class	OperationRosenblattTransformation1DPolyClenshawCurtis
class	OperationRosenblattTransformation1DPolyClenshawCurtisBoundary
class	OperationRosenblattTransformationBspline
	keep applying marginalize to function until it's reduced to only 1 dimension More...
class	OperationRosenblattTransformationBsplineBoundary
	keep applying marginalize to function until it's reduced to only 1 dimension More...
class	OperationRosenblattTransformationBsplineClenshawCurtis
	keep applying marginalize to function until it's reduced to only 1 dimension More...
class	OperationRosenblattTransformationKDE
	Do transformation in all dimensions. More...
class	OperationRosenblattTransformationLinear
	keep applying marginalize to function until it's reduced to only 1 dimension More...
class	OperationRosenblattTransformationModBspline
	keep applying marginalize to function until it's reduced to only 1 dimension More...
class	OperationRosenblattTransformationModBsplineClenshawCurtis
	keep applying marginalize to function until it's reduced to only 1 dimension More...
class	OperationRosenblattTransformationModPoly
	keep applying marginalize to function until it's reduced to only 1 dimension More...
class	OperationRosenblattTransformationModPolyClenshawCurtis
	keep applying marginalize to function until it's reduced to only 1 dimension More...
class	OperationRosenblattTransformationPoly
	keep applying marginalize to function until it's reduced to only 1 dimension More...
class	OperationRosenblattTransformationPolyBoundary
	keep applying marginalize to function until it's reduced to only 1 dimension More...
class	OperationRosenblattTransformationPolyClenshawCurtis
	keep applying marginalize to function until it's reduced to only 1 dimension More...
class	OperationRosenblattTransformationPolyClenshawCurtisBoundary
	keep applying marginalize to function until it's reduced to only 1 dimension More...
class	OperationTest
	Operation the tests the function that is applied the current Sparse sgpp::base::Grid at a given point. More...
class	OperationTestLinear
	This class implements OperationTest for a grids with linear basis ansatzfunctions without boundaries. More...
class	OperationTestLinearBoundary
	This class implements OperationTest for a grids with linear basis ansatzfunctions with boundaries. More...
class	OperationTestLinearStretched
	This class implements OperationTest for a grids with linearstretched basis ansatzfunctions without boundaries. More...
class	OperationTestLinearStretchedBoundary
	This class implements OperationTest for a grids with linear basis ansatzfunctions with boundaries. More...
class	OperationTestModBspline
	This class implements OperationTest for a grids with modified bspline basis functions with a certain degree. More...
class	OperationTestModLinear
	This class implements sgpp::base::OperationEval for a grids with mod linear basis ansatzfunctions with. More...
class	OperationTestModPoly
	This class implements OperationTest for a grids with mod poly basis ansatzfunctions with. More...
class	OperationTestModWavelet
	This class implements OperationTest for a grid with mod wavelet basis ansatzfunctions. More...
class	OperationTestPoly
	This class implements OperationTest for a grids with poly basis ansatzfunctions with. More...
class	OperationTestPrewavelet
	This class implements OperationTest for a grids with prewavelet basis ansatzfunctions without boundaries. More...
class	OperationTransformation1D
	Sample 1D Probability Density Function. More...
struct	ParallelConfiguration
	Struct that stores all the configuration information for parallelization with ScaLAPACK. More...
class	PartitioningTool
	The methods in this class calculate size and offset of a segment for a partition of a domain. More...
class	PendingMPIRequest
class	PiecewiseConstantSmoothedRegressionSystemMatrix
	Class that implements the virtual class OperationMatrix for the application of classification for the Systemmatrix by using a density function. More...
class	PolynomialChaosExpansion
	a PCE object providing different methods to calculate the PCE coefficients and evaluating the expansion More...
class	PrimalDualSVM
	Implementation of a support vector machine in primal formulation which additionally stores support vectors. More...
class	RefinementHandler
class	RefinementMonitor
	Superclass for refinement monitors. More...
class	RefinementMonitorConvergence
	A monitor to decide if a learning algorithm has converged. More...
class	RefinementMonitorFactory
	Factory to create refinement monitors. More...
class	RefinementMonitorPeriodic
	A monitor that decides whether refinements should be performed using a simple periodic approach: After at least a certain amount of instances has arrived, the monitor will allow a new refinement. More...
struct	RefinementResult
	Structure to hold the grid modifications for a refinement cycle for one class. More...
struct	RefinementResultNetworkMessage
	Packet wrapped in an UPDATE_GRID MPI_Packet, containing segmented changes for a specified class. More...
struct	RefinementResultSystemMatrixNetworkMessage
	Packet wrapped in a RefinementResultNetwork Message that contains additional information required when updating the system matrix. More...
class	RegressionLearner
	The RegressionLearner class Solves a regression problem with continuous target vector. More...
struct	RegularizationConfiguration
class	RegularizationTypeParser
class	ResidualScore
	Metric that is based on a residual score of the model. More...
class	RosenblattTransformation
struct	RosenblattTransformationConfig
	Configuration structure for Rosenblatt transformation including default values. More...
class	RoundRobinScheduler
class	RuleOfThumb
class	SampleProvider
	SampleProvider is an abstraction for object that provide sample data from various sources for example datasets from files (ARFF, CSV) or synthetic datasets generated by sampling functions ( Friedmann datasets). More...
class	Scorer
	Base class for supervised learning used to fit a model and quantify accuracy using a sgpp::datadriven::Metric with either testing or cross validation. More...
struct	ScorerConfiguration
	Set of parameters to define a scorer instance. More...
class	ScorerFactory
	Factory to build the scorer. More...
class	ScorerMetricTypeParser
	Convenience class to convert strings to sgpp::datadriven::ScorerMetricType or sgpp::datadriven::RegularizationMetricType and generate string representations for values of sgpp::datadriven::ScorerMetricType or sgpp::datadriven::RegularizationMetricType. More...
class	ScottsRule
struct	SGDEConfiguration
class	SilvermansRule
class	SortedDataset
	Dataset that can be ordered. Accessing the included DataMatrix might invalidate the order. More...
class	SparseGridDensityEstimator
class	SparseGridDensityEstimatorConfiguration
class	SparseGridMiner
	SparseGridMiner models the entire mining process for data mining with sparse grids. More...
class	SparseGridMinerCrossValidation
	SparseGridMinerCrossValidation models a datamining process that involves cross validation to validate the accuracy of the model itself. More...
class	SparseGridMinerSplitting
	SparseGridMiner models a datamining process that involves a dataset that is first split into validation and training data. More...
class	SparseGridMinerSplittingTwoDatasets
	SparseGridMinerSplittingTwoDatasets models a datamining process that involves two input datasets that are first split into validation and training data. More...
struct	StencilConfiguration
class	StreamingBSplineOCLKernelImpl
class	StreamingBSplineOCLKernelSourceBuilder
class	SubspaceNodeCombined
class	SubspaceNodeSimple
class	SystemMatrixDensityRatioEstimation
	Class that implements the virtual class base::OperationMatrix for the application of density ratio estimation for SystemMatrixDRE. More...
class	SystemMatrixLeastSquaresIdentity
	Class that implements the virtual class base::OperationMatrix for the application of classification for the Systemmatrix. More...
class	TestsetConfiguration
class	TunableParameter
class	UniversalMinerFactory
	Concrete Factory that builds an instance of sgpp::datadriven::SparseGridMiner for the fitting task specified by the configuration. More...
struct	VectorHash
	Hash to make an unordered_set over an vector of size_t's possible. More...
struct	VisualizationGeneralConfig
struct	VisualizationParameters
class	VisualizationTypesParser
	Convenience class to convert strings to sgpp::datadriven::VisualizationTypesParser and generate string representations for values of sgpp::datadriven::VisualizationFileType. More...
class	Visualizer
class	VisualizerClassification
class	VisualizerConfiguration
class	VisualizerDensityEstimation
class	VisualizerDummy
class	ZeroCrossingRefinementFunctor
	Zero-crossing-based refinement uses zero crossings of the difference PDFS f_1 - f_2 to determine areas of interest for the refinement process. More...

Typedefs
typedef std::vector< LevelIndexPair >	LevelIndexVector
	Vector that holds level index pairs for every dimensions.

Enumerations
enum class	BandwidthOptimizationType { NONE , SILVERMANSRULE , SCOTTSRULE , MAXIMUMLIKELIHOOD }
enum class	DataSourceFileType { NONE , ARFF , CSV }
	Supported file types for sgpp::datadriven::FileSampleProvider. More...
enum class	DataSourceShufflingType { random , sequential }
	Enumeration of all supported shuffling types used to permute samples in a dataset. More...
enum class	DataTransformationType { NONE , ROSENBLATT }
	Supported transformation types for sgpp::datadriven::DataTransformation. More...
enum class	DensityEstimationType { CG , Decomposition }
enum class	distributionType {   Normal , Beta , Uniform , Exponential ,   Gamma }
enum class	FitterType {   RegressionLeastSquares , DensityEstimation , DensityRatioEstimation , DensityDifferenceEstimation ,   Classification }
	Different fitter scenarios have different default values and support different operations. More...
enum class	InternalPrecision { Float , Double }
enum class	KernelType { GAUSSIAN , EPANECHNIKOV }
enum class	LearnerMode { LEARN , LEARNCOMPARE , LEARNTEST }
enum class	MakePositiveCandidateSearchAlgorithm { FullGrid , Intersections , HybridFullIntersections , IntersectionsJoin }
enum class	MakePositiveInterpolationAlgorithm { SetToZero , InterpolateExp , InterpolateBoundaries1d , InterpolateFunction }
enum class	MatrixDecompositionType {   LU , Eigen , Chol , DenseIchol ,   OrthoAdapt , SMW_ortho , SMW_chol }
enum	MPI_COMMAND_ID {   NULL_COMMAND , UPDATE_GRID , MERGE_GRID , ASSIGN_BATCH ,   COMPUTE_UPDATE_SYSTEM_MATRIX_DECOMPOSITION , SHUTDOWN , WORKER_SHUTDOWN_SUCCESS }
	Different commands sent over MPI to allow the receiver to identify the message's contents. More...
enum class	OperationMultipleEvalMPIType { NONE , MASTERSLAVE , HPX }
enum class	OperationMultipleEvalSubType {   DEFAULT , SIMPLE , COMBINED , OCL ,   OCLFASTMP , OCLMP , OCLMASKMP , OCLOPT ,   OCLUNIFIED , CUDA }
enum class	OperationMultipleEvalType {   DEFAULT , STREAMING , SUBSPACELINEAR , ADAPTIVE ,   MORTONORDER , SCALAPACK }
enum	RefinementResultsUpdateType { ADDED_GRID_POINTS_LIST , DELETED_GRID_POINTS_LIST , SYSTEM_MATRIX_DECOMPOSITION }
	The type of message received in a UPDATE_GRID message type. More...
enum class	RegularizationMetricType { mse , nll , accuracy , residual }
enum class	RegularizationType {   Identity , Laplace , Diagonal , Lasso ,   ElasticNet , GroupLasso }
enum class	ScorerMetricType { mse , nll , accuracy }
	Enumeration of all supported metrics used to quantify approximation quality of a trained model. More...
enum class	StencilType {   DirectNeighbour , AllHierarchicalParent , NextHierarchicalParent , Block ,   None }
enum	TaskType { TRAIN_FROM_BATCH , RECOMPUTE_SYSTEM_MATRIX_DECOMPOSITION }
	Used for the MPI Task Scheduler to differentiate between assigning tasks of different types. More...
enum class	VisualizationFileType { CSV , json }

Functions
DensityOCLMultiPlatform::OperationDensity *	createDensityOCLMultiPlatformConfigured (base::Grid &grid, size_t dimension, double lambda, base::OCLOperationConfiguration *parameters, size_t platform_id, size_t device_id)
DensityOCLMultiPlatform::OperationDensity *	createDensityOCLMultiPlatformConfigured (base::Grid &grid, size_t dimension, double lambda, std::string opencl_conf)
	Generates opencl density multiplication operation.
DensityOCLMultiPlatform::OperationDensity *	createDensityOCLMultiPlatformConfigured (base::Grid &grid, size_t dimension, double lambda, std::string opencl_conf, size_t platform_id, size_t device_id)
	Generates opencl density multiplication operation given opencl device and configuration file.
DensityOCLMultiPlatform::OperationDensity *	createDensityOCLMultiPlatformConfigured (int *gridpoints, size_t gridsize, size_t dimension, double lambda, base::OCLOperationConfiguration *parameters, size_t platform_id, size_t device_id)
DensityOCLMultiPlatform::OperationDensity *	createDensityOCLMultiPlatformConfigured (int *gridpoints, size_t gridsize, size_t dimension, double lambda, std::string opencl_conf, size_t platform_id, size_t device_id)
	Generates opencl density multiplication operation given opencl device and a serialized grid.
DensityOCLMultiPlatform::OperationCreateGraphOCL *	createNearestNeighborGraphConfigured (base::DataMatrix &dataset, size_t k, size_t dimensions, std::string opencl_conf)
	Generates the k nearest neighbors graph creation.
DensityOCLMultiPlatform::OperationCreateGraphOCL *	createNearestNeighborGraphConfigured (base::DataMatrix &dataset, size_t k, size_t dimensions, std::string opencl_conf, size_t platformid, size_t devicdeid)
	Generates the k nearest neighbors graph creation using a specific opencl device and a datamatrix.
DensityOCLMultiPlatform::OperationCreateGraphOCL *	createNearestNeighborGraphConfigured (double *dataset, size_t dataset_size, size_t k, size_t dimensions, sgpp::base::OCLOperationConfiguration *parameters, size_t platformid, size_t deviceid)
DensityOCLMultiPlatform::OperationCreateGraphOCL *	createNearestNeighborGraphConfigured (double *dataset, size_t dataset_size, size_t k, size_t dimensions, std::string opencl_conf, size_t platformid, size_t devicdeid)
	Generates the k nearest neighbors graph creation using a specific opencl device and a double vector.
base::OperationMultipleEval *	createStreamingBSplineOCLConfigured (base::Grid &grid, base::DataMatrix &dataset, sgpp::datadriven::OperationMultipleEvalConfiguration &configuration)
base::OperationMultipleEval *	createStreamingModOCLFastMultiPlatformConfigured (base::Grid &grid, base::DataMatrix &dataset, sgpp::datadriven::OperationMultipleEvalConfiguration &configuration)
base::OperationMultipleEval *	createStreamingModOCLMaskMultiPlatformConfigured (base::Grid &grid, base::DataMatrix &dataset, sgpp::datadriven::OperationMultipleEvalConfiguration &configuration)
base::OperationMultipleEval *	createStreamingModOCLOptConfigured (base::Grid &grid, base::DataMatrix &dataset, sgpp::datadriven::OperationMultipleEvalConfiguration &configuration)
base::OperationMultipleEval *	createStreamingModOCLUnifiedConfigured (base::Grid &grid, base::DataMatrix &dataset, sgpp::datadriven::OperationMultipleEvalConfiguration &configuration)
base::OperationMultipleEval *	createStreamingOCLMultiPlatformConfigured (base::Grid &grid, base::DataMatrix &dataset, sgpp::datadriven::OperationMultipleEvalConfiguration &configuration)
	Factory method for creating a new instance of this variant of OperationMultipleEval.
DensityOCLMultiPlatform::OperationPruneGraphOCL *	pruneNearestNeighborGraphConfigured (base::Grid &grid, size_t dimensions, base::DataVector &alpha, base::DataMatrix &data, double treshold, size_t k, std::string opencl_conf)
	Generates the graph pruning operation.
DensityOCLMultiPlatform::OperationPruneGraphOCL *	pruneNearestNeighborGraphConfigured (base::Grid &grid, size_t dimensions, base::DataVector &alpha, base::DataMatrix &data, double treshold, size_t k, std::string opencl_conf, size_t platformid, size_t deviceid)
	Generates the graph pruning operation for a specific opencl device.
DensityOCLMultiPlatform::OperationPruneGraphOCL *	pruneNearestNeighborGraphConfigured (int *gridpoints, size_t gridsize, size_t dimensions, double *alpha, base::DataMatrix &data, double treshold, size_t k, sgpp::base::OCLOperationConfiguration *parameters, size_t platformid, size_t deviceid)
DensityOCLMultiPlatform::OperationPruneGraphOCL *	pruneNearestNeighborGraphConfigured (int *gridpoints, size_t gridsize, size_t dimensions, double *alpha, base::DataMatrix &data, double treshold, size_t k, std::string opencl_conf, size_t platformid, size_t deviceid)
	Generates the graph pruning operation for a specific opencl device using a serialized grid.
template<class BASIS >
void	test_calculateROCcurve (base::GridStorage *storage, BASIS &basis, base::DataVector &alpha, base::DataMatrix &data, base::DataVector &classes, base::DataVector &thresholds, base::DataMatrix &ROC_curve)
	Returns the number of correctly classified instances in data without boundaries.
template<class BASIS >
double	test_dataset (base::GridStorage *storage, BASIS &basis, base::DataVector &alpha, base::DataMatrix &data, base::DataVector &classes)
	Returns the number of correctly classified instances in data without boundaries.
template<class BASIS >
double	test_dataset_mse (base::GridStorage *storage, BASIS &basis, base::DataVector &alpha, base::DataMatrix &data, base::DataVector &refValues)
	Returns the MSE for given functions values at the evaluation points.
template<class BASIS >
double	test_datasetWithCharacteristicNumber (base::GridStorage *storage, BASIS &basis, base::DataVector &alpha, base::DataMatrix &data, base::DataVector &classes, base::DataVector &charaNumbers, double threshold)
	Returns the number of correctly classified instances in data without boundaries.
void	validate (boost::any &v, const std::vector< std::string > &values, sgpp::datadriven::LearnerMode *target_type, int)
void	validate (boost::any &v, const std::vector< std::string > &values, sgpp::datadriven::OperationMultipleEvalSubType *target_type, int)
void	validate (boost::any &v, const std::vector< std::string > &values, sgpp::datadriven::OperationMultipleEvalType *target_type, int)

Variables
const int	csrc_ = 7
const int	ctxt_ = 1
const int	dtype_ = 0
const int	kDescriptor_ = 9
const std::string	keyDecompositionType = "decomposition"
const std::string	keyDensityEstimationConfiguration = "densityEstimationConfiguration"
const std::string	keyFilepath = "filepath"
const std::string	keyGridConfiguration = "gridConfiguration"
const std::string	keyGridDimension = "dimension"
const std::string	keyGridLevel = "level"
const std::string	keyGridType = "type"
const std::string	keyRegularizationConfiguration = "regularizationConfiguration"
const std::string	keyRegularizationStrength = "lambda"
const int	lld_ = 8
const char *const	lowerTriangular = "L"
const int	m_ = 2
const int	mb_ = 4
const int	n_ = 3
const int	nb_ = 5
const char *const	pblasConjugate = "C"
const char *const	pblasNoTranspose = "N"
const char *const	pblasTranspose = "T"
const int	rsrc_ = 6
const char *const	upperTriangular = "U"

Typedef Documentation

LevelIndexVector

typedef std::vector<LevelIndexPair> sgpp::datadriven::LevelIndexVector

Vector that holds level index pairs for every dimensions.

Enumeration Type Documentation

BandwidthOptimizationType

enum class sgpp::datadriven::BandwidthOptimizationType

strong

Enumerator
NONE
SILVERMANSRULE
SCOTTSRULE
MAXIMUMLIKELIHOOD

DataSourceFileType

enum class sgpp::datadriven::DataSourceFileType

strong

Supported file types for sgpp::datadriven::FileSampleProvider.

Enumerator
NONE
ARFF
CSV

DataSourceShufflingType

enum class sgpp::datadriven::DataSourceShufflingType

strong

Enumeration of all supported shuffling types used to permute samples in a dataset.

An entry exists for each object that derives from sgpp::datadriven::DataShufflingFunctor. Used for configuration and factory methods.

Enumerator
random
sequential

DataTransformationType

enum class sgpp::datadriven::DataTransformationType

strong

Supported transformation types for sgpp::datadriven::DataTransformation.

Enumerator
NONE
ROSENBLATT

DensityEstimationType

enum class sgpp::datadriven::DensityEstimationType

strong

Enumerator
CG
Decomposition

distributionType

enum class sgpp::datadriven::distributionType

strong

Enumerator
Normal
Beta
Uniform
Exponential
Gamma

FitterType

enum class sgpp::datadriven::FitterType

strong

Different fitter scenarios have different default values and support different operations.

Enumerator
RegressionLeastSquares
DensityEstimation
DensityRatioEstimation
DensityDifferenceEstimation
Classification

InternalPrecision

enum class sgpp::datadriven::InternalPrecision

strong

Enumerator
Float
Double

KernelType

enum class sgpp::datadriven::KernelType

strong

Enumerator
GAUSSIAN
EPANECHNIKOV

LearnerMode

enum class sgpp::datadriven::LearnerMode

strong

Enumerator
LEARN
LEARNCOMPARE
LEARNTEST

MakePositiveCandidateSearchAlgorithm

enum class sgpp::datadriven::MakePositiveCandidateSearchAlgorithm

strong

Enumerator
FullGrid
Intersections
HybridFullIntersections
IntersectionsJoin

MakePositiveInterpolationAlgorithm

enum class sgpp::datadriven::MakePositiveInterpolationAlgorithm

strong

Enumerator
SetToZero
InterpolateExp
InterpolateBoundaries1d
InterpolateFunction

MatrixDecompositionType

enum class sgpp::datadriven::MatrixDecompositionType

strong

Enumerator
LU
Eigen
Chol
DenseIchol
OrthoAdapt
SMW_ortho
SMW_chol

MPI_COMMAND_ID

enum sgpp::datadriven::MPI_COMMAND_ID

Different commands sent over MPI to allow the receiver to identify the message's contents.

Enumerator
NULL_COMMAND	Used to identify packets where the command id has not been set.
UPDATE_GRID	A packet that contains changes to the grid or the system matrix.
MERGE_GRID	A packet that contains results from a training.
ASSIGN_BATCH	A packet that assigns a batch with specified parameters to a worker.
COMPUTE_UPDATE_SYSTEM_MATRIX_DECOMPOSITION	A packet that assigns updating the system matrix decomposition to a worker.
SHUTDOWN	A packet that instructs a worker to shutdown its MPI facilities after completing all requests.
WORKER_SHUTDOWN_SUCCESS	A confirmation packet sent by a worker to acknowledge all requests were completed.

OperationMultipleEvalMPIType

enum class sgpp::datadriven::OperationMultipleEvalMPIType

strong

Enumerator
NONE
MASTERSLAVE
HPX

OperationMultipleEvalSubType

enum class sgpp::datadriven::OperationMultipleEvalSubType

strong

Enumerator
DEFAULT
SIMPLE
COMBINED
OCL
OCLFASTMP
OCLMP
OCLMASKMP
OCLOPT
OCLUNIFIED
CUDA

OperationMultipleEvalType

enum class sgpp::datadriven::OperationMultipleEvalType

strong

Enumerator
DEFAULT
STREAMING
SUBSPACELINEAR
ADAPTIVE
MORTONORDER
SCALAPACK

RefinementResultsUpdateType

enum sgpp::datadriven::RefinementResultsUpdateType

The type of message received in a UPDATE_GRID message type.

Enumerator
ADDED_GRID_POINTS_LIST	Packet contains a set of coordinates for newly created grid points.
DELETED_GRID_POINTS_LIST	Packet contains a set of indices for grid points which were deleted.
SYSTEM_MATRIX_DECOMPOSITION	Packet contains a part of an updated system matrix decomposition.

RegularizationMetricType

enum class sgpp::datadriven::RegularizationMetricType

strong

Enumerator
mse
nll
accuracy
residual

RegularizationType

enum class sgpp::datadriven::RegularizationType

strong

Enumerator
Identity
Laplace
Diagonal
Lasso
ElasticNet
GroupLasso

ScorerMetricType

enum class sgpp::datadriven::ScorerMetricType

strong

Enumeration of all supported metrics used to quantify approximation quality of a trained model.

An entry exists for each object that derives from sgpp::datadriven::Metric. Used for configuration and factory methods.

Enumerator
mse
nll
accuracy

StencilType

enum class sgpp::datadriven::StencilType

strong

Enumerator
DirectNeighbour
AllHierarchicalParent
NextHierarchicalParent
Block
None

TaskType

enum sgpp::datadriven::TaskType

Used for the MPI Task Scheduler to differentiate between assigning tasks of different types.

Enumerator
TRAIN_FROM_BATCH
RECOMPUTE_SYSTEM_MATRIX_DECOMPOSITION

VisualizationFileType

enum class sgpp::datadriven::VisualizationFileType

strong

Enumerator
CSV
json

Function Documentation

createDensityOCLMultiPlatformConfigured() [1/5]

DensityOCLMultiPlatform::OperationDensity * sgpp::datadriven::createDensityOCLMultiPlatformConfigured	(	base::Grid &	grid,
		size_t	dimension,
		double	lambda,
		base::OCLOperationConfiguration *	parameters,
		size_t	platform_id,
		size_t	device_id
	)

References grid(), lambda, and sgpp::datadriven::DensityOCLMultiPlatform::OperationDensity::load_default_parameters().

Referenced by sgpp::datadriven::ClusteringOCL::OperationClusteringOCL< T >::calculate_clusters(), sgpp::datadriven::clusteringmpi::DensityRhsWorker::DensityRhsWorker(), sgpp::datadriven::clusteringmpi::DensityWorker::DensityWorker(), main(), and main().

createDensityOCLMultiPlatformConfigured() [2/5]

sgpp::datadriven::DensityOCLMultiPlatform::OperationDensity * sgpp::datadriven::createDensityOCLMultiPlatformConfigured	(	base::Grid &	grid,
		size_t	dimension,
		double	lambda,
		std::string	opencl_conf
	)

Generates opencl density multiplication operation.

References json::DictNode::contains(), grid(), lambda, and sgpp::datadriven::DensityOCLMultiPlatform::OperationDensity::load_default_parameters().

createDensityOCLMultiPlatformConfigured() [3/5]

sgpp::datadriven::DensityOCLMultiPlatform::OperationDensity * sgpp::datadriven::createDensityOCLMultiPlatformConfigured	(	base::Grid &	grid,
		size_t	dimension,
		double	lambda,
		std::string	opencl_conf,
		size_t	platform_id,
		size_t	device_id
	)

Generates opencl density multiplication operation given opencl device and configuration file.

References grid(), lambda, and sgpp::datadriven::DensityOCLMultiPlatform::OperationDensity::load_default_parameters().

createDensityOCLMultiPlatformConfigured() [4/5]

DensityOCLMultiPlatform::OperationDensity * sgpp::datadriven::createDensityOCLMultiPlatformConfigured	(	int *	gridpoints,
		size_t	gridsize,
		size_t	dimension,
		double	lambda,
		base::OCLOperationConfiguration *	parameters,
		size_t	platform_id,
		size_t	device_id
	)

References lambda, and sgpp::datadriven::DensityOCLMultiPlatform::OperationDensity::load_default_parameters().

createDensityOCLMultiPlatformConfigured() [5/5]

sgpp::datadriven::DensityOCLMultiPlatform::OperationDensity * sgpp::datadriven::createDensityOCLMultiPlatformConfigured	(	int *	gridpoints,
		size_t	gridsize,
		size_t	dimension,
		double	lambda,
		std::string	opencl_conf,
		size_t	platform_id,
		size_t	device_id
	)

Generates opencl density multiplication operation given opencl device and a serialized grid.

References lambda, and sgpp::datadriven::DensityOCLMultiPlatform::OperationDensity::load_default_parameters().

createNearestNeighborGraphConfigured() [1/4]

DensityOCLMultiPlatform::OperationCreateGraphOCL * sgpp::datadriven::createNearestNeighborGraphConfigured	(	base::DataMatrix &	dataset,
		size_t	k,
		size_t	dimensions,
		std::string	opencl_conf
	)

Generates the k nearest neighbors graph creation.

References json::DictNode::contains(), dataset, and sgpp::datadriven::DensityOCLMultiPlatform::OperationCreateGraphOCL::load_default_parameters().

createNearestNeighborGraphConfigured() [2/4]

DensityOCLMultiPlatform::OperationCreateGraphOCL * sgpp::datadriven::createNearestNeighborGraphConfigured	(	base::DataMatrix &	dataset,
		size_t	k,
		size_t	dimensions,
		std::string	opencl_conf,
		size_t	platformid,
		size_t	deviceid
	)

Generates the k nearest neighbors graph creation using a specific opencl device and a datamatrix.

References dataset, and sgpp::datadriven::DensityOCLMultiPlatform::OperationCreateGraphOCL::load_default_parameters().

Referenced by sgpp::datadriven::ClusteringOCL::OperationClusteringOCL< T >::calculate_clusters(), sgpp::datadriven::clusteringmpi::GraphCreationWorker::GraphCreationWorker(), main(), and sgpp::datadriven::clusteringmpi::PrunedGraphCreationWorker::PrunedGraphCreationWorker().

createNearestNeighborGraphConfigured() [3/4]

DensityOCLMultiPlatform::OperationCreateGraphOCL * sgpp::datadriven::createNearestNeighborGraphConfigured	(	double *	dataset,
		size_t	dataset_size,
		size_t	k,
		size_t	dimensions,
		sgpp::base::OCLOperationConfiguration *	parameters,
		size_t	platformid,
		size_t	deviceid
	)

References dataset, and sgpp::datadriven::DensityOCLMultiPlatform::OperationCreateGraphOCL::load_default_parameters().

createNearestNeighborGraphConfigured() [4/4]

DensityOCLMultiPlatform::OperationCreateGraphOCL * sgpp::datadriven::createNearestNeighborGraphConfigured	(	double *	dataset,
		size_t	dataset_size,
		size_t	k,
		size_t	dimensions,
		std::string	opencl_conf,
		size_t	platformid,
		size_t	deviceid
	)

Generates the k nearest neighbors graph creation using a specific opencl device and a double vector.

References dataset, and sgpp::datadriven::DensityOCLMultiPlatform::OperationCreateGraphOCL::load_default_parameters().

createStreamingBSplineOCLConfigured()

base::OperationMultipleEval * sgpp::datadriven::createStreamingBSplineOCLConfigured	(	base::Grid &	grid,
		base::DataMatrix &	dataset,
		sgpp::datadriven::OperationMultipleEvalConfiguration &	configuration
	)

References dataset, sgpp::datadriven::OperationMultipleEvalConfiguration::getParameters(), and grid().

Referenced by sgpp::op_factory::createOperationMultipleEval().

createStreamingModOCLFastMultiPlatformConfigured()

base::OperationMultipleEval * sgpp::datadriven::createStreamingModOCLFastMultiPlatformConfigured	(	base::Grid &	grid,
		base::DataMatrix &	dataset,
		sgpp::datadriven::OperationMultipleEvalConfiguration &	configuration
	)

References sgpp::datadriven::StreamingModOCLFastMultiPlatform::Configuration::augmentDefaultParameters(), dataset, sgpp::datadriven::OperationMultipleEvalConfiguration::getParameters(), and grid().

Referenced by sgpp::op_factory::createOperationMultipleEval().

createStreamingModOCLMaskMultiPlatformConfigured()

base::OperationMultipleEval * sgpp::datadriven::createStreamingModOCLMaskMultiPlatformConfigured	(	base::Grid &	grid,
		base::DataMatrix &	dataset,
		sgpp::datadriven::OperationMultipleEvalConfiguration &	configuration
	)

References sgpp::datadriven::StreamingModOCLMaskMultiPlatform::Configuration::augmentDefaultParameters(), dataset, sgpp::datadriven::OperationMultipleEvalConfiguration::getParameters(), and grid().

Referenced by sgpp::op_factory::createOperationMultipleEval().

createStreamingModOCLOptConfigured()

base::OperationMultipleEval * sgpp::datadriven::createStreamingModOCLOptConfigured	(	base::Grid &	grid,
		base::DataMatrix &	dataset,
		sgpp::datadriven::OperationMultipleEvalConfiguration &	configuration
	)

References sgpp::datadriven::StreamingModOCLOpt::Configuration::augmentDefaultParameters(), dataset, sgpp::datadriven::OperationMultipleEvalConfiguration::getParameters(), and grid().

Referenced by sgpp::op_factory::createOperationMultipleEval().

createStreamingModOCLUnifiedConfigured()

base::OperationMultipleEval * sgpp::datadriven::createStreamingModOCLUnifiedConfigured	(	base::Grid &	grid,
		base::DataMatrix &	dataset,
		sgpp::datadriven::OperationMultipleEvalConfiguration &	configuration
	)

References sgpp::datadriven::StreamingModOCLUnified::Configuration::augmentDefaultParameters(), dataset, sgpp::datadriven::OperationMultipleEvalConfiguration::getParameters(), and grid().

createStreamingOCLMultiPlatformConfigured()

base::OperationMultipleEval * sgpp::datadriven::createStreamingOCLMultiPlatformConfigured	(	base::Grid &	grid,
		base::DataMatrix &	dataset,
		sgpp::datadriven::OperationMultipleEvalConfiguration &	configuration
	)

Factory method for creating a new instance of this variant of OperationMultipleEval.

This factory method configures the resulting object by using the parameters of the provided configuration. If no parameters are provided, the default parameter values are used. If a configuration is provided, but some entries were not set, this class adds the missing entries with their default values. This class is the non-templated entry point for the templated inner objects. Templates are used to implement different floating point precision.

See also

OperationMultiEvalStreamingOCLMultiPlatform

Parameters

grid	The sparse grid to evaluate
dataset	The datapoints to evaluate
configuration	Configuration that may contain a parameter object for configuration details

References sgpp::datadriven::StreamingOCLMultiPlatform::Configuration::augmentDefaultParameters(), dataset, sgpp::datadriven::OperationMultipleEvalConfiguration::getParameters(), and grid().

Referenced by sgpp::op_factory::createOperationMultipleEval().

pruneNearestNeighborGraphConfigured() [1/4]

sgpp::datadriven::DensityOCLMultiPlatform::OperationPruneGraphOCL * sgpp::datadriven::pruneNearestNeighborGraphConfigured	(	base::Grid &	grid,
		size_t	dimensions,
		base::DataVector &	alpha,
		base::DataMatrix &	data,
		double	treshold,
		size_t	k,
		std::string	opencl_conf
	)

Generates the graph pruning operation.

References alpha, json::DictNode::contains(), grid(), and sgpp::datadriven::DensityOCLMultiPlatform::OperationPruneGraphOCL::load_default_parameters().

pruneNearestNeighborGraphConfigured() [2/4]

sgpp::datadriven::DensityOCLMultiPlatform::OperationPruneGraphOCL * sgpp::datadriven::pruneNearestNeighborGraphConfigured	(	base::Grid &	grid,
		size_t	dimensions,
		base::DataVector &	alpha,
		base::DataMatrix &	data,
		double	treshold,
		size_t	k,
		std::string	opencl_conf,
		size_t	platformid,
		size_t	deviceid
	)

Generates the graph pruning operation for a specific opencl device.

References alpha, grid(), and sgpp::datadriven::DensityOCLMultiPlatform::OperationPruneGraphOCL::load_default_parameters().

Referenced by sgpp::datadriven::ClusteringOCL::OperationClusteringOCL< T >::calculate_clusters(), main(), and sgpp::datadriven::clusteringmpi::PrunedGraphCreationWorker::PrunedGraphCreationWorker().

pruneNearestNeighborGraphConfigured() [3/4]

DensityOCLMultiPlatform::OperationPruneGraphOCL * sgpp::datadriven::pruneNearestNeighborGraphConfigured	(	int *	gridpoints,
		size_t	gridsize,
		size_t	dimensions,
		double *	alpha,
		base::DataMatrix &	data,
		double	treshold,
		size_t	k,
		sgpp::base::OCLOperationConfiguration *	parameters,
		size_t	platformid,
		size_t	deviceid
	)

References alpha, and sgpp::datadriven::DensityOCLMultiPlatform::OperationPruneGraphOCL::load_default_parameters().

pruneNearestNeighborGraphConfigured() [4/4]

sgpp::datadriven::DensityOCLMultiPlatform::OperationPruneGraphOCL * sgpp::datadriven::pruneNearestNeighborGraphConfigured	(	int *	gridpoints,
		size_t	gridsize,
		size_t	dimensions,
		double *	alpha,
		base::DataMatrix &	data,
		double	treshold,
		size_t	k,
		std::string	opencl_conf,
		size_t	platformid,
		size_t	deviceid
	)

Generates the graph pruning operation for a specific opencl device using a serialized grid.

References alpha, and sgpp::datadriven::DensityOCLMultiPlatform::OperationPruneGraphOCL::load_default_parameters().

test_calculateROCcurve()

template<class BASIS >

void sgpp::datadriven::test_calculateROCcurve	(	base::GridStorage *	storage,
		BASIS &	basis,
		base::DataVector &	alpha,
		base::DataMatrix &	data,
		base::DataVector &	classes,
		base::DataVector &	thresholds,
		base::DataMatrix &	ROC_curve
	)

Returns the number of correctly classified instances in data without boundaries.

Parameters

storage	base::GridStorage object that contains the grid points
basis	reference to class that implements to current basis
alpha	the coefficients of the grid points
data	the data the should be tested
classes	the reference classes
thresholds	the thresholds (between -1.0 and 1.0) for calculating the ROC curve
ROC_curve	DataMatrix into which the ROC curve is stored

References alpha, sgpp::base::DataVector::get(), sgpp::base::DataMatrix::getNrows(), sgpp::base::DataVector::getSize(), sgpp::base::DataMatrix::resize(), sgpp::base::DataMatrix::set(), and test_datasetWithCharacteristicNumber().

Referenced by sgpp::datadriven::OperationTestLinear::calculateROCcurve(), sgpp::datadriven::OperationTestLinearBoundary::calculateROCcurve(), sgpp::datadriven::OperationTestLinearStretched::calculateROCcurve(), sgpp::datadriven::OperationTestLinearStretchedBoundary::calculateROCcurve(), sgpp::datadriven::OperationTestModBspline::calculateROCcurve(), sgpp::datadriven::OperationTestModLinear::calculateROCcurve(), sgpp::datadriven::OperationTestModPoly::calculateROCcurve(), sgpp::datadriven::OperationTestModWavelet::calculateROCcurve(), sgpp::datadriven::OperationTestPoly::calculateROCcurve(), and sgpp::datadriven::OperationTestPrewavelet::calculateROCcurve().

test_dataset()

template<class BASIS >

double sgpp::datadriven::test_dataset	(	base::GridStorage *	storage,
		BASIS &	basis,
		base::DataVector &	alpha,
		base::DataMatrix &	data,
		base::DataVector &	classes
	)

Returns the number of correctly classified instances in data without boundaries.

Parameters

storage	base::GridStorage object that contains the grid points
basis	reference to class that implements to current basis
alpha	the coefficients of the grid points
data	the data the should be tested
classes	the reference classes

References alpha.

Referenced by sgpp::datadriven::OperationTestLinearStretchedBoundary::test(), sgpp::datadriven::OperationTestModBspline::test(), sgpp::datadriven::OperationTestModPoly::test(), sgpp::datadriven::OperationTestPoly::test(), sgpp::datadriven::OperationTestLinear::test(), sgpp::datadriven::OperationTestLinearBoundary::test(), sgpp::datadriven::OperationTestLinearStretched::test(), sgpp::datadriven::OperationTestModLinear::test(), sgpp::datadriven::OperationTestModWavelet::test(), and sgpp::datadriven::OperationTestPrewavelet::test().

test_dataset_mse()

template<class BASIS >

double sgpp::datadriven::test_dataset_mse	(	base::GridStorage *	storage,
		BASIS &	basis,
		base::DataVector &	alpha,
		base::DataMatrix &	data,
		base::DataVector &	refValues
	)

Returns the MSE for given functions values at the evaluation points.

Parameters

storage	base::GridStorage object that contains the grid points
basis	reference to class that implements to current basis
alpha	the coefficients of the grid points
data	the data the should be tested
refValues	the function values at the evaluation points

References alpha, sgpp::base::DataVector::getSize(), mse, sgpp::base::DataVector::sqr(), sgpp::base::DataVector::sub(), and sgpp::base::DataVector::sum().

Referenced by sgpp::datadriven::OperationTestLinearStretchedBoundary::testMSE(), sgpp::datadriven::OperationTestModBspline::testMSE(), sgpp::datadriven::OperationTestModPoly::testMSE(), sgpp::datadriven::OperationTestPoly::testMSE(), sgpp::datadriven::OperationTestLinear::testMSE(), sgpp::datadriven::OperationTestLinearBoundary::testMSE(), sgpp::datadriven::OperationTestLinearStretched::testMSE(), sgpp::datadriven::OperationTestModLinear::testMSE(), sgpp::datadriven::OperationTestModWavelet::testMSE(), and sgpp::datadriven::OperationTestPrewavelet::testMSE().

test_datasetWithCharacteristicNumber()

template<class BASIS >

double sgpp::datadriven::test_datasetWithCharacteristicNumber	(	base::GridStorage *	storage,
		BASIS &	basis,
		base::DataVector &	alpha,
		base::DataMatrix &	data,
		base::DataVector &	classes,
		base::DataVector &	charaNumbers,
		double	threshold
	)

Returns the number of correctly classified instances in data without boundaries.

Parameters

storage	base::GridStorage object that contains the grid points
basis	reference to class that implements to current basis
alpha	the coefficients of the grid points
data	the data the should be tested
classes	the reference classes
charaNumbers	the number of true positives, true negatives, false positives, false negatives (Vector of length 4)
threshold	threshold which decides if an instance belongs a given class

References alpha, sgpp::base::DataVector::getSize(), and sgpp::base::DataVector::set().

Referenced by test_calculateROCcurve(), sgpp::datadriven::OperationTestLinear::testWithCharacteristicNumber(), sgpp::datadriven::OperationTestLinearBoundary::testWithCharacteristicNumber(), sgpp::datadriven::OperationTestLinearStretched::testWithCharacteristicNumber(), sgpp::datadriven::OperationTestLinearStretchedBoundary::testWithCharacteristicNumber(), sgpp::datadriven::OperationTestModBspline::testWithCharacteristicNumber(), sgpp::datadriven::OperationTestModLinear::testWithCharacteristicNumber(), sgpp::datadriven::OperationTestModPoly::testWithCharacteristicNumber(), sgpp::datadriven::OperationTestModWavelet::testWithCharacteristicNumber(), sgpp::datadriven::OperationTestPoly::testWithCharacteristicNumber(), and sgpp::datadriven::OperationTestPrewavelet::testWithCharacteristicNumber().

validate() [1/3]

void sgpp::datadriven::validate	(	boost::any &	v,
		const std::vector< std::string > &	values,
		sgpp::datadriven::LearnerMode *	target_type,
		int
	)

References LEARN, LEARNCOMPARE, and LEARNTEST.

validate() [2/3]

void sgpp::datadriven::validate	(	boost::any &	v,
		const std::vector< std::string > &	values,
		sgpp::datadriven::OperationMultipleEvalSubType *	target_type,
		int
	)

References COMBINED, DEFAULT, OCL, OCLFASTMP, OCLMASKMP, OCLMP, and SIMPLE.

validate() [3/3]

void sgpp::datadriven::validate	(	boost::any &	v,
		const std::vector< std::string > &	values,
		sgpp::datadriven::OperationMultipleEvalType *	target_type,
		int
	)

References DEFAULT, STREAMING, and SUBSPACELINEAR.

Variable Documentation

csrc_

const int sgpp::datadriven::csrc_ = 7

Referenced by sgpp::datadriven::DataMatrixDistributed::DataMatrixDistributed().

ctxt_

const int sgpp::datadriven::ctxt_ = 1

Referenced by sgpp::datadriven::DataMatrixDistributed::DataMatrixDistributed().

dtype_

const int sgpp::datadriven::dtype_ = 0

Referenced by sgpp::datadriven::DataMatrixDistributed::DataMatrixDistributed().

kDescriptor_

const int sgpp::datadriven::kDescriptor_ = 9

keyDecompositionType

const std::string sgpp::datadriven::keyDecompositionType = "decomposition"

Referenced by sgpp::datadriven::DBMatDatabase::putDataMatrix().

keyDensityEstimationConfiguration

const std::string sgpp::datadriven::keyDensityEstimationConfiguration = "densityEstimationConfiguration"

Referenced by sgpp::datadriven::DBMatDatabase::putDataMatrix().

keyFilepath

const std::string sgpp::datadriven::keyFilepath = "filepath"

Referenced by sgpp::datadriven::DBMatDatabase::getBaseDataMatrix(), sgpp::datadriven::DBMatDatabase::getDataMatrix(), and sgpp::datadriven::DBMatDatabase::putDataMatrix().

keyGridConfiguration

const std::string sgpp::datadriven::keyGridConfiguration = "gridConfiguration"

Referenced by sgpp::datadriven::DBMatDatabase::getBaseDataMatrix(), and sgpp::datadriven::DBMatDatabase::putDataMatrix().

keyGridDimension

const std::string sgpp::datadriven::keyGridDimension = "dimension"

Referenced by sgpp::datadriven::DBMatDatabase::getBaseDataMatrix(), and sgpp::datadriven::DBMatDatabase::putDataMatrix().

keyGridLevel

const std::string sgpp::datadriven::keyGridLevel = "level"

Referenced by sgpp::datadriven::DBMatDatabase::getBaseDataMatrix(), and sgpp::datadriven::DBMatDatabase::putDataMatrix().

keyGridType

const std::string sgpp::datadriven::keyGridType = "type"

Referenced by sgpp::datadriven::DBMatDatabase::putDataMatrix().

keyRegularizationConfiguration

const std::string sgpp::datadriven::keyRegularizationConfiguration = "regularizationConfiguration"

Referenced by sgpp::datadriven::DBMatDatabase::putDataMatrix().

keyRegularizationStrength

const std::string sgpp::datadriven::keyRegularizationStrength = "lambda"

Referenced by sgpp::datadriven::DBMatDatabase::putDataMatrix().

lld_

const int sgpp::datadriven::lld_ = 8

Referenced by sgpp::datadriven::DataMatrixDistributed::copyFrom(), sgpp::datadriven::DataMatrixDistributed::DataMatrixDistributed(), and sgpp::datadriven::DataMatrixDistributed::resize().

lowerTriangular

const char* const sgpp::datadriven::lowerTriangular = "L"

Referenced by sgpp::datadriven::DataMatrixDistributed::solveCholesky().

m_

const int sgpp::datadriven::m_ = 2

Referenced by sgpp::datadriven::DataMatrixDistributed::copyFrom(), sgpp::datadriven::DataMatrixDistributed::DataMatrixDistributed(), and sgpp::datadriven::DataMatrixDistributed::resize().

mb_

const int sgpp::datadriven::mb_ = 4

Referenced by sgpp::datadriven::DataMatrixDistributed::DataMatrixDistributed().

n_

const int sgpp::datadriven::n_ = 3

Referenced by sgpp::datadriven::DataMatrixDistributed::copyFrom(), sgpp::datadriven::DataMatrixDistributed::DataMatrixDistributed(), and sgpp::datadriven::DataMatrixDistributed::resize().

nb_

const int sgpp::datadriven::nb_ = 5

Referenced by sgpp::datadriven::DataMatrixDistributed::DataMatrixDistributed().

pblasConjugate

const char* const sgpp::datadriven::pblasConjugate = "C"

pblasNoTranspose

const char* const sgpp::datadriven::pblasNoTranspose = "N"

Referenced by sgpp::datadriven::DataMatrixDistributed::add(), sgpp::datadriven::DataMatrixDistributed::mult(), and sgpp::datadriven::DataMatrixDistributed::mult().

pblasTranspose

const char* const sgpp::datadriven::pblasTranspose = "T"

Referenced by sgpp::datadriven::DataMatrixDistributed::add(), sgpp::datadriven::DataMatrixDistributed::mult(), and sgpp::datadriven::DataMatrixDistributed::mult().

rsrc_

const int sgpp::datadriven::rsrc_ = 6

Referenced by sgpp::datadriven::DataMatrixDistributed::DataMatrixDistributed().

upperTriangular

const char* const sgpp::datadriven::upperTriangular = "U"

Referenced by sgpp::datadriven::DataMatrixDistributed::solveCholesky().