SG++
python.learner.Classifier.Classifier Class Reference

The class implements the abstract methods from Learner and allows to accomplish basic classification tasks. More...

Inheritance diagram for python.learner.Classifier.Classifier:

Public Member Functions

def evalError (self, data, alpha)
 Evaluate classification accuracy as percent of correct classified data points. More...
 
def refineGrid (self)
 Refines grid with the number of points as specified in corresponding TrainingSpecification object. More...
 
def updateResults (self, alpha, trainSubset, testSubset=None)
 Update different statistics about training progress. More...
 

Detailed Description

The class implements the abstract methods from Learner and allows to accomplish basic classification tasks.

Member Function Documentation

def python.learner.Classifier.Classifier.evalError (   self,
  data,
  alpha 
)

Evaluate classification accuracy as percent of correct classified data points.

Parameters
dataDataContainer dataset
alphaDataVector alpha-vector
Returns
: percent of correct classified data, 0 if data set is empty

References sgpp::op_factory.createOperationTest(), python.uq.operations.forcePositivity.localFullGridSearch.LocalFullGrid.grid, python.uq.operations.forcePositivity.localHierarchicalIntersectionSearch.LocalHierarchicalIntersectionCandidates.grid, sgpp::datadriven::OperationDensitySampling1DLinear.grid, sgpp::datadriven::OperationRosenblattTransformation1DLinear.grid, sgpp::datadriven::OperationInverseRosenblattTransformation1DLinear.grid, python.uq.operations.forcePositivity.operationMakePositive.OperationMakePositive.grid, sgpp::datadriven::LogDensitySystemMatrix.grid, sgpp::base::OperationMultipleEval.grid, python.uq.operations.forcePositivity.operationMakePositiveFast.OperationMakePositiveFast.grid, sgpp::datadriven::PiecewiseConstantSmoothedRegressionSystemMatrix.grid, sgpp::datadriven::DMSystemMatrix.grid, sgpp::datadriven::LearnerSVM.grid, sgpp::datadriven::MultipleEvalHPX::LocalityMultiplier.grid, sgpp::datadriven::LearnerBase.grid, sgpp::datadriven::OperationDensityMarginalizeLinear.grid, sgpp::datadriven::OperationDensityRejectionSamplingLinear.grid, sgpp::datadriven::OperationDensityConditionalLinear.grid, sgpp::base::OperationHierarchisationModFundamentalSpline.grid, sgpp::base::OperationHierarchisationFundamentalSpline.grid, sgpp::datadriven::OperationDensitySamplingLinear.grid, sgpp::datadriven::SystemMatrixLeastSquaresIdentity.grid, sgpp::datadriven::OperationInverseRosenblattTransformationLinear.grid, sgpp::datadriven::OperationRosenblattTransformationLinear.grid, python.uq.learner.Learner.Learner.grid, sgpp::datadriven::OperationDensityMargTo1DLinear.grid, python.learner.Learner.Learner.grid, sgpp::optimization::IterativeGridGenerator.grid, sgpp::datadriven::AlgorithmAdaBoostBase.grid, sgpp::optimization::OperationMultipleHierarchisationWavelet.grid, sgpp::optimization::OperationMultipleHierarchisationWaveletBoundary.grid, sgpp::optimization::OperationMultipleHierarchisationModWavelet.grid, sgpp::optimization::OperationMultipleHierarchisationBspline.grid, sgpp::optimization::OperationMultipleHierarchisationBsplineBoundary.grid, sgpp::optimization::OperationMultipleHierarchisationLinear.grid, sgpp::optimization::OperationMultipleHierarchisationLinearBoundary.grid, sgpp::optimization::OperationMultipleHierarchisationModBspline.grid, sgpp::optimization::OperationMultipleHierarchisationModLinear.grid, sgpp::optimization::OperationMultipleHierarchisationFundamentalSpline.grid, sgpp::optimization::OperationMultipleHierarchisationLinearClenshawCurtis.grid, sgpp::base::DehierarchisationFundamentalSpline.grid, sgpp::base::HierarchisationFundamentalSpline.grid, sgpp::optimization::OperationMultipleHierarchisationBsplineClenshawCurtis.grid, sgpp::base::HierarchisationModFundamentalSpline.grid, sgpp::optimization::OperationMultipleHierarchisationModBsplineClenshawCurtis.grid, sgpp::optimization::OperationMultipleHierarchisationModFundamentalSpline.grid, sgpp::base::DehierarchisationModFundamentalSpline.grid, sgpp::base::OperationQuadratureMC.grid, python.controller.CheckpointController.CheckpointController.grid, sgpp::optimization::InterpolantScalarFunctionGradient.grid, sgpp::optimization::InterpolantScalarFunctionHessian.grid, sgpp::optimization::InterpolantVectorFunctionGradient.grid, sgpp::optimization::InterpolantScalarFunction.grid, sgpp::optimization::InterpolantVectorFunction.grid, sgpp::optimization::InterpolantVectorFunctionHessian.grid, sgpp::combigrid::LTwoScalarProductHashMapNakBsplineBoundaryCombigrid.grid, sgpp::quadrature::OperationQuadratureMCAdvanced.grid, sgpp::base::ForwardSelectorRefinementIndicator.grid, sgpp::base::ImpurityRefinementIndicator.grid, sgpp::datadriven::ModelFittingBase.grid, sgpp::datadriven::LearnerSGD.grid, sgpp::optimization::HierarchisationSLE.grid, sgpp::datadriven::DBMatOffline.grid, python.uq.operations.forcePositivity.localFullGridSearch.LocalFullGridCandidates.grid, sgpp::datadriven::RegressionLearner.grid, sgpp::datadriven::LearnerSGDE.grid, and python.tools.Matrix.grid.

Referenced by python.learner.Classifier.Classifier.updateResults(), python.learner.Regressor.Regressor.updateResults(), python.uq.learner.Interpolant.Interpolant.updateResults(), and python.uq.learner.Regressor.Regressor.updateResults().

def python.learner.Classifier.Classifier.refineGrid (   self)

Refines grid with the number of points as specified in corresponding TrainingSpecification object.

References sgpp::datadriven::clusteringmpi::DensityWorker.alpha, sgpp::datadriven::LogDensitySystemMatrix.alpha, sgpp::datadriven::clusteringmpi::PrunedGraphCreationWorker.alpha, python.learner.solver.CGSolver.CGSolver.alpha, sgpp::datadriven::LearnerBase.alpha, sgpp::datadriven::OperationMultiEvalCuda.alpha, sgpp::base::SurplusRefinementFunctor.alpha, sgpp::base::SurplusCoarseningFunctor.alpha, sgpp::base::SurplusVolumeRefinementFunctor.alpha, sgpp::base::SurplusVolumeCoarseningFunctor.alpha, python.uq.learner.Regressor.Regressor.alpha, python.uq.dists.Beta.Beta.alpha(), python.uq.learner.Learner.Learner.alpha, python.learner.Learner.Learner.alpha, sgpp::optimization::InterpolantScalarFunctionGradient.alpha, sgpp::optimization::InterpolantScalarFunctionHessian.alpha, sgpp::optimization::InterpolantVectorFunctionGradient.alpha, sgpp::optimization::InterpolantScalarFunction.alpha, sgpp::optimization::InterpolantVectorFunction.alpha, python.uq.learner.Interpolant.Interpolant.alpha, sgpp::optimization::InterpolantVectorFunctionHessian.alpha, sgpp::optimization::optimizer::NelderMead.alpha, sgpp::datadriven::DBMatOnlineDE.alpha, sgpp::optimization::optimizer::NLCG.alpha, sgpp::datadriven::LearnerSGD.alpha, sgpp::datadriven::ModelFittingBase.alpha, sgpp::datadriven::LearnerSGDE.alpha, python.learner.solver.LinearSolver.LinearSolver.notifyEventControllers(), python.uq.learner.Learner.Learner.notifyEventControllers(), python.learner.Learner.Learner.notifyEventControllers(), and python.uq.operations.discretizeProduct.refine().

Referenced by python.uq.learner.Regressor.Regressor.learnData(), python.learner.Learner.Learner.learnData(), and python.learner.Learner.Learner.learnDataWithTest().


The documentation for this class was generated from the following file: