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sgpp::datadriven Namespace Reference

Namespaces

 PiecewiseConstantRegression
 
 streamingBSplineOCL
 
 StreamingModOCLFastMultiPlatform
 
 StreamingModOCLMaskMultiPlatform
 
 StreamingModOCLOpt
 
 StreamingModOCLUnified
 
 StreamingOCLMultiPlatform
 
 x86simple
 

Classes

class  AbstractOperationMultipleEvalSubspace
 
class  AlgorithmAdaBoostBase
 
class  AlgorithmAdaBoostIdentity
 
class  ArffFileSampleProvider
 
class  ARFFTools
 Class that provides functionality to read ARFF files. More...
 
class  BatchLearner
 The Batchlearner learns the data provided as input in batches. More...
 
struct  ClassificatorQuality
 struct to encapsulate the classsifiers quality by its characteristic numbers More...
 
class  CrossValidation
 
struct  CrossvalidationForRegularizationConfiguration
 
class  DataBasedRefinementFunctor
 Data based refinement uses data points to find refinement candidates. More...
 
class  DataMiningConfigJsonParser
 
class  DataMiningConfigurationLeastSquares
 
class  Dataset
 
class  DatasetGenerator
 
class  DatasetTools
 
class  DataSource
 
class  DataSourceBuilder
 
class  DataSourceConfig
 
class  DataSourceIterator
 
struct  DataSourceStateConfig
 
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  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  FileSampleDecorator
 
class  FileSampleProvider
 
class  Friedman1Generator
 
class  Friedman2Generator
 
class  Friedman3Generator
 
class  GaussianKDE
 
class  GridPointBasedRefinementFunctor
 Grid Point based refinement for classification problems solved by a SG density estimation approach. More...
 
class  GzipFileSampleDecorator
 
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...
 
class  LearnerLeastSquaresIdentity
 This class implements standard sparse grid regression with an Identity matrix as regularization operator. More...
 
class  LearnerPiecewiseConstantSmoothedRegression
 
class  LearnerScenario
 
class  LearnerSGDE
 
class  LearnerSGDEConfiguration
 
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  LogDensitySystemMatrix
 Class that implements the virtual class OperationMatrix for the application of classification for the Systemmatrix by using a density function. More...
 
class  MetaLearner
 
class  Metric
 Metrics. More...
 
class  ModelFittingBase
 
class  ModelFittingLeastSquares
 This class implements standard sparse grid regression with an Identity matrix as regularization operator. More...
 
class  MSE
 
class  MultiGridRefinementFunctor
 Abstract super-class for refinement functors operating on multiple grids. More...
 
class  MultiSurplusRefinementFunctor
 Wrapper of SurplusRefinementFunctor for multi grid scenarios. 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  OperationDensityMargTo1DLinear
 keep applying marginalize to function until it's reduced to only 1 dimension 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  OperationInverseRosenblattTransformation1DLinear
 
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  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  OperationMultipleEvalSubspaceCombined
 
class  OperationMultipleEvalSubspaceSimple
 
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  OperationRosenblattTransformation1DLinear
 
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  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  PiecewiseConstantSmoothedRegressionMetaLearner
 
class  PiecewiseConstantSmoothedRegressionSystemMatrix
 Class that implements the virtual class OperationMatrix for the application of classification for the Systemmatrix by using a density function. More...
 
class  RandomShufflingFunctor
 
struct  RegularizationConfiguration
 
class  SampleProvider
 
class  ShufflingFunctor
 
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  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...
 

Enumerations

enum  FileType { NONE, ARFF }
 
enum  FittingSolverState { FittingSolverState::refine, FittingSolverState::solve }
 
enum  InternalPrecision { InternalPrecision::Float, InternalPrecision::Double }
 
enum  LearnerMode { LearnerMode::LEARN, LearnerMode::LEARNCOMPARE, LearnerMode::LEARNTEST }
 
enum  OperationMultipleEvalMPIType { OperationMultipleEvalMPIType::NONE, OperationMultipleEvalMPIType::MASTERSLAVE }
 
enum  OperationMultipleEvalSubType {
  OperationMultipleEvalSubType::DEFAULT, OperationMultipleEvalSubType::SIMPLE, OperationMultipleEvalSubType::COMBINED, OperationMultipleEvalSubType::OCL,
  OperationMultipleEvalSubType::OCLFASTMP, OperationMultipleEvalSubType::OCLMP, OperationMultipleEvalSubType::OCLMASKMP, OperationMultipleEvalSubType::OCLOPT,
  OperationMultipleEvalSubType::OCLUNIFIED
}
 
enum  OperationMultipleEvalType { OperationMultipleEvalType::DEFAULT, OperationMultipleEvalType::STREAMING, OperationMultipleEvalType::SUBSPACELINEAR, OperationMultipleEvalType::ADAPTIVE }
 
enum  RegularizationType { RegularizationType::Identity, RegularizationType::Laplace }
 

Functions

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)
 
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_
 

Enumeration Type Documentation

Enumerator
NONE 
ARFF 
Enumerator
refine 
solve 
Enumerator
Float 
Double 
Enumerator
LEARN 
LEARNCOMPARE 
LEARNTEST 
Enumerator
NONE 
MASTERSLAVE 
Enumerator
DEFAULT 
SIMPLE 
COMBINED 
OCL 
OCLFASTMP 
OCLMP 
OCLMASKMP 
OCLOPT 
OCLUNIFIED 
Enumerator
DEFAULT 
STREAMING 
SUBSPACELINEAR 
ADAPTIVE 
Enumerator
Identity 
Laplace 

Function Documentation

base::OperationMultipleEval * sgpp::datadriven::createStreamingModOCLUnifiedConfigured ( base::Grid &  grid,
base::DataMatrix &  dataset,
sgpp::datadriven::OperationMultipleEvalConfiguration configuration 
)
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_dataset_mse ( base::GridStorage *  storage,
BASIS &  basis,
base::DataVector &  alpha,
base::DataMatrix &  data,
base::DataVector &  refValues 
)
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(), sgpp::base::DataVector::resize(), 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   
)

References DEFAULT, STREAMING, and SUBSPACELINEAR.

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   
)

References LEARN, LEARNCOMPARE, and LEARNTEST.

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_