SG++-Doxygen-Documentation
sgpp::datadriven Namespace Reference

Namespaces

 clusteringmpi
 
 ClusteringOCL
 
 DBMatOfflineFactory
 factories to build the specialization of the DBMatOffline objects.
 
 DBMatOnlineDEFactory
 
 DensityOCLMultiPlatform
 
 MultipleEvalHPX
 
 PiecewiseConstantRegression
 
 streamingBSplineOCL
 
 StreamingModOCLFastMultiPlatform
 
 StreamingModOCLMaskMultiPlatform
 
 StreamingModOCLOpt
 
 StreamingModOCLUnified
 
 StreamingOCLMultiPlatform
 
 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  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  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  ClassificationLearner
 The ClassificationLearner class Solves a classification problem. More...
 
class  ClassificationMinerFactory
 Concrete Factory that builds an instance of sgpp::datadriven::SparseGridMiner for classification. More...
 
struct  ClassificatorQuality
 struct to encapsulate the classsifiers quality by its characteristic numbers More...
 
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...
 
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  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  DBMatDatabase
 A database class to store and retrieve online matrix decompositions for the sparse grid density estimation. More...
 
class  DBMatDecompMatrixSolver
 
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  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  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  DBMatOnlineDEChol
 
class  DBMatOnlineDEOrthoAdapt
 
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  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  DMSystemMatrix
 Class that implements the virtual class base::OperationMatrix for the application of classification 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  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
 
class  GeneralGridTypeParser
 Parser class to parse a general grid type into a GeneralGridType enum type and vice versa. More...
 
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  GridTypeParser
 
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  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  ModelFittingDensityEstimationOnOff
 Fitter object that encapsulates the usage of sparse grid density estimation 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  OperationMultiEvalStreamingBSplineOCL
 
class  OperationMultiEvalStreamingModOCLFastMultiPlatform
 
class  OperationMultiEvalStreamingModOCLMaskMultiPlatform
 
class  OperationMultiEvalStreamingModOCLOpt
 
class  OperationMultiEvalStreamingModOCLUnified
 
class  OperationMultipleEvalConfiguration
 
class  OperationMultipleEvalMatrix
 wrapper class for matrix multiplication for use in solver 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...
 
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  PrimalDualSVM
 Implementation of a support vector machine in primal formulation which additionally stores support vectors. More...
 
class  RefinementFunctorTypeParser
 
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  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 and generate string representations for values of sgpp::datadriven::ScorerMetricType. More...
 
class  ScottsRule
 
struct  SGDEConfiguration
 
class  SilvermansRule
 
class  SLESolverTypeParser
 Convenience class to convert strings to sgpp::solver::SLESolverType and generate string representations for values of sgpp::solver::SLESolverType. More...
 
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  StreamingBSplineOCLKernelImpl
 
class  StreamingBSplineOCLKernelSourceBuilder
 
class  StringTokenizer
 
class  SubspaceNodeCombined
 
class  SubspaceNodeSimple
 
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...
 
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< LevelIndexPairLevelIndexVector
 Vector that holds level index pairs for every dimensions. More...
 

Enumerations

enum  BandwidthOptimizationType { BandwidthOptimizationType::NONE, BandwidthOptimizationType::SILVERMANSRULE, BandwidthOptimizationType::SCOTTSRULE, BandwidthOptimizationType::MAXIMUMLIKELIHOOD }
 
enum  DataSourceFileType { DataSourceFileType::NONE, DataSourceFileType::ARFF, DataSourceFileType::CSV }
 Supported file types for sgpp::datadriven::FileSampleProvider. More...
 
enum  DataSourceShufflingType { DataSourceShufflingType::random, DataSourceShufflingType::sequential }
 Enumeration of all supported shuffling types used to permute samples in a dataset. More...
 
enum  DataTransformationType { DataTransformationType::NONE, DataTransformationType::ROSENBLATT }
 Supported transformation types for sgpp::datadriven::DataTransformation. More...
 
enum  DensityEstimationType { DensityEstimationType::CG, DensityEstimationType::Decomposition }
 
enum  FitterType { FitterType::RegressionLeastSquares, FitterType::DensityEstimation }
 Different fitter scenarios have different default values and support different operations. More...
 
enum  InternalPrecision { InternalPrecision::Float, InternalPrecision::Double }
 
enum  KernelType { KernelType::GAUSSIAN, KernelType::EPANECHNIKOV }
 
enum  LearnerMode { LearnerMode::LEARN, LearnerMode::LEARNCOMPARE, LearnerMode::LEARNTEST }
 
enum  MakePositiveCandidateSearchAlgorithm { MakePositiveCandidateSearchAlgorithm::FullGrid, MakePositiveCandidateSearchAlgorithm::Intersections, MakePositiveCandidateSearchAlgorithm::HybridFullIntersections, MakePositiveCandidateSearchAlgorithm::IntersectionsJoin }
 
enum  MakePositiveInterpolationAlgorithm { MakePositiveInterpolationAlgorithm::SetToZero, MakePositiveInterpolationAlgorithm::InterpolateExp, MakePositiveInterpolationAlgorithm::InterpolateBoundaries1d, MakePositiveInterpolationAlgorithm::InterpolateFunction }
 
enum  MatrixDecompositionType {
  MatrixDecompositionType::LU, MatrixDecompositionType::Eigen, MatrixDecompositionType::Chol, MatrixDecompositionType::DenseIchol,
  MatrixDecompositionType::OrthoAdapt
}
 
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  OperationMultipleEvalMPIType { OperationMultipleEvalMPIType::NONE, OperationMultipleEvalMPIType::MASTERSLAVE, OperationMultipleEvalMPIType::HPX }
 
enum  OperationMultipleEvalSubType {
  OperationMultipleEvalSubType::DEFAULT, OperationMultipleEvalSubType::SIMPLE, OperationMultipleEvalSubType::COMBINED, OperationMultipleEvalSubType::OCL,
  OperationMultipleEvalSubType::OCLFASTMP, OperationMultipleEvalSubType::OCLMP, OperationMultipleEvalSubType::OCLMASKMP, OperationMultipleEvalSubType::OCLOPT,
  OperationMultipleEvalSubType::OCLUNIFIED, OperationMultipleEvalSubType::CUDA
}
 
enum  OperationMultipleEvalType {
  OperationMultipleEvalType::DEFAULT, OperationMultipleEvalType::STREAMING, OperationMultipleEvalType::SUBSPACELINEAR, OperationMultipleEvalType::ADAPTIVE,
  OperationMultipleEvalType::MORTONORDER
}
 
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  RegularizationType {
  RegularizationType::Identity, RegularizationType::Laplace, RegularizationType::Diagonal, RegularizationType::Lasso,
  RegularizationType::ElasticNet, RegularizationType::GroupLasso
}
 
enum  ScorerMetricType { ScorerMetricType::mse, ScorerMetricType::nll, ScorerMetricType::accuracy }
 Enumeration of all supported metrics used to quantify approximation quality of a trained model. More...
 
enum  TaskType { TRAIN_FROM_BATCH, RECOMPUTE_SYSTEM_MATRIX_DECOMPOSITION }
 Used for the MPI Task Scheduler to differentiate between assigning tasks of different types. More...
 

Functions

DensityOCLMultiPlatform::OperationDensitycreateDensityOCLMultiPlatformConfigured (base::Grid &grid, size_t dimension, double lambda, base::OCLOperationConfiguration *parameters, size_t platform_id, size_t device_id)
 
DensityOCLMultiPlatform::OperationDensitycreateDensityOCLMultiPlatformConfigured (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. More...
 
DensityOCLMultiPlatform::OperationDensitycreateDensityOCLMultiPlatformConfigured (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. More...
 
DensityOCLMultiPlatform::OperationDensitycreateDensityOCLMultiPlatformConfigured (int *gridpoints, size_t gridsize, size_t dimension, double lambda, base::OCLOperationConfiguration *parameters, size_t platform_id, size_t device_id)
 
DensityOCLMultiPlatform::OperationDensitycreateDensityOCLMultiPlatformConfigured (base::Grid &grid, size_t dimension, double lambda, std::string opencl_conf)
 Generates opencl density multiplication operation. More...
 
DensityOCLMultiPlatform::OperationCreateGraphOCLcreateNearestNeighborGraphConfigured (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. More...
 
DensityOCLMultiPlatform::OperationCreateGraphOCLcreateNearestNeighborGraphConfigured (double *dataset, size_t dataset_size, size_t k, size_t dimensions, sgpp::base::OCLOperationConfiguration *parameters, size_t platformid, size_t deviceid)
 
DensityOCLMultiPlatform::OperationCreateGraphOCLcreateNearestNeighborGraphConfigured (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. More...
 
DensityOCLMultiPlatform::OperationCreateGraphOCLcreateNearestNeighborGraphConfigured (base::DataMatrix &dataset, size_t k, size_t dimensions, std::string opencl_conf)
 Generates the k nearest neighbors graph creation. More...
 
base::OperationMultipleEvalcreateStreamingBSplineOCLConfigured (base::Grid &grid, base::DataMatrix &dataset, sgpp::datadriven::OperationMultipleEvalConfiguration &configuration)
 
base::OperationMultipleEvalcreateStreamingModOCLFastMultiPlatformConfigured (base::Grid &grid, base::DataMatrix &dataset, sgpp::datadriven::OperationMultipleEvalConfiguration &configuration)
 
base::OperationMultipleEvalcreateStreamingModOCLMaskMultiPlatformConfigured (base::Grid &grid, base::DataMatrix &dataset, sgpp::datadriven::OperationMultipleEvalConfiguration &configuration)
 
base::OperationMultipleEvalcreateStreamingModOCLOptConfigured (base::Grid &grid, base::DataMatrix &dataset, sgpp::datadriven::OperationMultipleEvalConfiguration &configuration)
 
base::OperationMultipleEvalcreateStreamingModOCLUnifiedConfigured (base::Grid &grid, base::DataMatrix &dataset, sgpp::datadriven::OperationMultipleEvalConfiguration &configuration)
 
base::OperationMultipleEvalcreateStreamingOCLMultiPlatformConfigured (base::Grid &grid, base::DataMatrix &dataset, sgpp::datadriven::OperationMultipleEvalConfiguration &configuration)
 Factory method for creating a new instance of this variant of OperationMultipleEval. More...
 
DensityOCLMultiPlatform::OperationPruneGraphOCLpruneNearestNeighborGraphConfigured (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. More...
 
DensityOCLMultiPlatform::OperationPruneGraphOCLpruneNearestNeighborGraphConfigured (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. More...
 
DensityOCLMultiPlatform::OperationPruneGraphOCLpruneNearestNeighborGraphConfigured (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::OperationPruneGraphOCLpruneNearestNeighborGraphConfigured (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. More...
 
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. More...
 
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. More...
 
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. More...
 
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. More...
 
void validate (boost::any &v, const std::vector< std::string > &values, sgpp::datadriven::OperationMultipleEvalType *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::LearnerMode *target_type, int)
 

Variables

double execTime_
 execution time More...
 
double GByte_
 number of transferred Gbytes More...
 
double GFlop_
 number of executed Floating Point operations More...
 
bool isRegression_
 is regression selected More...
 
bool isTrained_
 is the grid trained More...
 
bool isVerbose_
 
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"
 

Typedef Documentation

Vector that holds level index pairs for every dimensions.

Enumeration Type Documentation

Enumerator
NONE 
SILVERMANSRULE 
SCOTTSRULE 
MAXIMUMLIKELIHOOD 

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

Enumerator
NONE 
ARFF 
CSV 

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 

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

Enumerator
NONE 
ROSENBLATT 
Enumerator
CG 
Decomposition 

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

Enumerator
RegressionLeastSquares 
DensityEstimation 
Enumerator
Float 
Double 
Enumerator
GAUSSIAN 
EPANECHNIKOV 
Enumerator
LEARN 
LEARNCOMPARE 
LEARNTEST 
Enumerator
FullGrid 
Intersections 
HybridFullIntersections 
IntersectionsJoin 
Enumerator
SetToZero 
InterpolateExp 
InterpolateBoundaries1d 
InterpolateFunction 
Enumerator
LU 
Eigen 
Chol 
DenseIchol 
OrthoAdapt 

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.

Enumerator
NONE 
MASTERSLAVE 
HPX 
Enumerator
DEFAULT 
SIMPLE 
COMBINED 
OCL 
OCLFASTMP 
OCLMP 
OCLMASKMP 
OCLOPT 
OCLUNIFIED 
CUDA 
Enumerator
DEFAULT 
STREAMING 
SUBSPACELINEAR 
ADAPTIVE 
MORTONORDER 

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.

Enumerator
Identity 
Laplace 
Diagonal 
Lasso 
ElasticNet 
GroupLasso 

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 

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

Enumerator
TRAIN_FROM_BATCH 
RECOMPUTE_SYSTEM_MATRIX_DECOMPOSITION 

Function Documentation

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().

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 python.utils.sg_projections::gridpoints, lambda, and sgpp::datadriven::DensityOCLMultiPlatform::OperationDensity::load_default_parameters().

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 
)
sgpp::datadriven::DensityOCLMultiPlatform::OperationDensity * sgpp::datadriven::createDensityOCLMultiPlatformConfigured ( base::Grid grid,
size_t  dimension,
double  lambda,
std::string  opencl_conf 
)
DensityOCLMultiPlatform::OperationCreateGraphOCL * sgpp::datadriven::createNearestNeighborGraphConfigured ( base::DataMatrix dataset,
size_t  k,
size_t  dimensions,
std::string  opencl_conf,
size_t  platformid,
size_t  deviceid 
)
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 
)
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().

DensityOCLMultiPlatform::OperationCreateGraphOCL * sgpp::datadriven::createNearestNeighborGraphConfigured ( base::DataMatrix dataset,
size_t  k,
size_t  dimensions,
std::string  opencl_conf 
)
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
gridThe sparse grid to evaluate
datasetThe datapoints to evaluate
configurationConfiguration 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().

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 
)
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, python.statsfileInfo::data, python.utils.sg_projections::gridpoints, and sgpp::datadriven::DensityOCLMultiPlatform::OperationPruneGraphOCL::load_default_parameters().

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 
)
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 
)
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 
)
template<class BASIS >
double sgpp::datadriven::test_dataset ( base::GridStorage storage,
BASIS &  basis,
base::DataVector alpha,
base::DataMatrix data,
base::DataVector classes 
)
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
storagebase::GridStorage object that contains the grid points
basisreference to class that implements to current basis
alphathe coefficients of the grid points
datathe data the should be tested
classesthe reference classes
charaNumbersthe number of true positives, true negatives, false positives, false negatives (Vector of length 4)
thresholdthreshold which decides if an instance belongs a given class

References sgpp::base::DataMatrix::getNcols(), sgpp::base::DataMatrix::getNrows(), sgpp::base::DataMatrix::getRow(), sgpp::base::DataVector::getSize(), python.statsfileInfo::i, chess::point, and sgpp::base::DataVector::set().

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

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

Variable Documentation

double sgpp::datadriven::execTime_

execution time

double sgpp::datadriven::GByte_

number of transferred Gbytes

double sgpp::datadriven::GFlop_

number of executed Floating Point operations

bool sgpp::datadriven::isRegression_

is regression selected

bool sgpp::datadriven::isTrained_

is the grid trained

bool sgpp::datadriven::isVerbose_
const std::string sgpp::datadriven::keyDecompositionType = "decomposition"
const std::string sgpp::datadriven::keyDensityEstimationConfiguration = "densityEstimationConfiguration"
const std::string sgpp::datadriven::keyFilepath = "filepath"
const std::string sgpp::datadriven::keyGridConfiguration = "gridConfiguration"
const std::string sgpp::datadriven::keyGridDimension = "dimension"
const std::string sgpp::datadriven::keyGridLevel = "level"
const std::string sgpp::datadriven::keyGridType = "type"
const std::string sgpp::datadriven::keyRegularizationConfiguration = "regularizationConfiguration"
const std::string sgpp::datadriven::keyRegularizationStrength = "lambda"