This class implements standard sparse grid regression with an arbitrary regularization operator.
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| Learner (sgpp::datadriven::RegularizationType ®ularization, const bool isRegression, const bool isVerbose=true) |
| Constructor. More...
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virtual | ~Learner () |
| Destructor. More...
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void | dumpFunction (std::string tFilename, size_t resolution) |
| simple dump of sparse grid function into file, e.g. More...
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void | dumpGrid (std::string tFilename) |
| simple dump of grid points into file, e.g. More...
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virtual double | getAccuracy (sgpp::base::DataMatrix &testDataset, const sgpp::base::DataVector &classesReference, const double threshold=0.0) |
| compute the accuracy for given testDataset. More...
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virtual double | getAccuracy (const sgpp::base::DataVector &classesComputed, const sgpp::base::DataVector &classesReference, const double threshold=0.0) |
| compute the accuracy for given testDataset. More...
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sgpp::base::DataVector & | getAlpha () |
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virtual ClassificatorQuality | getCassificatorQuality (sgpp::base::DataMatrix &testDataset, const sgpp::base::DataVector &classesReference, const double threshold=0.0) |
| compute the quality for given testDataset, classification ONLY! test is automatically called in order to determine the regression values of the current learner More...
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virtual ClassificatorQuality | getCassificatorQuality (const sgpp::base::DataVector &classesComputed, const sgpp::base::DataVector &classesReference, const double threshold=0.0) |
| compute the quality for given testDataset, classification ONLY! More...
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sgpp::base::Grid & | getGrid () |
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bool | getIsRegression () const |
| determines the current mode More...
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bool | getIsVerbose () const |
| determines the current verbose mode of learner More...
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std::vector< std::pair< size_t, double > > | getRefinementExecTimes () |
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| LearnerBase (const bool isRegression, const bool isVerbose=true) |
| Constructor. More...
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| LearnerBase (const LearnerBase ©Me) |
| Copy-Constructor. More...
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virtual void | multTranspose (sgpp::base::DataMatrix &dataset, sgpp::base::DataVector &multiplier, sgpp::base::DataVector &result) |
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virtual void | predict (sgpp::base::DataMatrix &testDataset, sgpp::base::DataVector &classesComputed) |
| executes a Regression test for a given dataset and returns the result More...
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void | setIsVerbose (const bool isVerbose) |
| sets the current verbose mode of learner More...
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void | setReuseCoefficients (bool reuseCoefficients) |
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void | setSolverVerbose (bool solverVerbose) |
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void | store (std::string tGridFilename, std::string tAlphaFilename) |
| store the grid and its current coefficients into files for further usage. More...
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virtual LearnerTiming | train (sgpp::base::DataMatrix &trainDataset, sgpp::base::DataVector &classes, const sgpp::base::RegularGridConfiguration &GridConfig, const sgpp::solver::SLESolverConfiguration &SolverConfigRefine, const sgpp::solver::SLESolverConfiguration &SolverConfigFinal, const sgpp::base::AdaptivityConfiguration &AdaptConfig, bool testAccDuringAdapt, const double lambdaRegularization, sgpp::base::DataMatrix *testDataset=nullptr, sgpp::base::DataVector *testClasses=nullptr) |
| Learning a dataset with spatially adaptive sparse grids. More...
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LearnerTiming | train (sgpp::base::DataMatrix &trainDataset, sgpp::base::DataVector &classes, const sgpp::base::RegularGridConfiguration &GridConfig, const sgpp::solver::SLESolverConfiguration &SolverConfig, const double lambdaRegularization) |
| Learning a dataset with regular sparse grids. More...
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virtual | ~LearnerBase () |
| Destructor. More...
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This class implements standard sparse grid regression with an arbitrary regularization operator.