SG++-Doxygen-Documentation
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Provides functionality for accomplishment of learning with cross-validation by generating a set of training data/validation data pairs from the set of files This class corresponds to the old doFoldf() method. More...
Public Member Functions | |
def | __init__ (self, dataContainer, level=1) |
Constructor. More... | |
Public Attributes | |
level | |
Provides functionality for accomplishment of learning with cross-validation by generating a set of training data/validation data pairs from the set of files This class corresponds to the old doFoldf() method.
def python.learner.folding.FilesFoldingPolicy.FilesFoldingPolicy.__init__ | ( | self, | |
dataContainer, | |||
level = 1 |
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) |
Constructor.
dataContainer | DataContainer with data set |
level | Integer folding level, default value: 1. This parameter is used for compatibility only. The folding level will be set to the number of files. |
python.learner.folding.FilesFoldingPolicy.FilesFoldingPolicy.level |
Referenced by python.uq.operations.forcePositivity.localFullGridSearch.LocalFullGrid.__eq__(), python.learner.folding.FoldingPolicy.FoldingPolicy.__next__(), python.uq.operations.forcePositivity.localFullGridSearch.LocalFullGrid.contains(), python.uq.operations.forcePositivity.localFullGridSearch.LocalFullGrid.containsDimx(), python.uq.learner.builder.GridDescriptor.GridDescriptor.createGrid(), python.uq.estimators.MarginalIntegralStrategy.MarginalIntegralStrategy.estimate(), python.uq.learner.builder.GridDescriptor.GridDescriptor.fromGrid(), python.uq.operations.forcePositivity.localFullGridSearch.LocalFullGrid.getLevelIndex(), python.uq.operations.forcePositivity.localFullGridSearch.LocalFullGrid.getMaxLevel(), python.uq.operations.forcePositivity.localFullGridSearch.LocalFullGrid.overlap(), python.uq.operations.forcePositivity.localFullGridSearch.LocalFullGrid.overlapDimx(), python.uq.operations.forcePositivity.localFullGridSearch.LocalFullGrid.transformToReferenceGrid(), python.uq.manager.ASGCStatistics.ASGCStatistics.updateResults(), python.uq.learner.SimulationLearner.SimulationLearner.updateResults(), python.uq.learner.builder.GridDescriptor.GridDescriptor.withLevel(), and python.uq.learner.builder.RegressorSpecificationDescriptor.FoldingDescriptor.withLevel().