SG++
python.learner.folding.FoldingPolicy.FoldingPolicy Class Reference

Abstract class for providing functionality for accomplishment of learning with cross-validation by generating a set of training data/validation data pairs. More...

Inheritance diagram for python.learner.folding.FoldingPolicy.FoldingPolicy:

Public Member Functions

def __init__ (self, dataset, level=1)
 Constructor. More...
 
def __iter__ (self)
 Implementation of iterator method iter() iterates through subsets. More...
 
def createFoldsets (self, dataContainer, validationIndeces)
 Create fold new data set Brings points given by validationIndeces together as test subset and the rest of points as train subset. More...
 
def next (self)
 Implementation of iterator method next() More...
 

Public Attributes

 dataFold
 List of partitioned data sets. More...
 
 dataset
 Dataset. More...
 
 level
 Folding level. More...
 
 seq
 Sequence of indices of points from data set. More...
 
 size
 Size of dataset. More...
 
 window
 Number of points in one subset. More...
 

Detailed Description

Abstract class for providing functionality for accomplishment of learning with cross-validation by generating a set of training data/validation data pairs.

Constructor & Destructor Documentation

def python.learner.folding.FoldingPolicy.FoldingPolicy.__init__ (   self,
  dataset,
  level = 1 
)

Constructor.

Parameters
datasetDataContainer with data set
levelInteger folding level, default value: 1

Member Function Documentation

def python.learner.folding.FoldingPolicy.FoldingPolicy.__iter__ (   self)

Implementation of iterator method iter() iterates through subsets.

References python.learner.folding.FoldingPolicy.FoldingPolicy.next(), and python.data.DataContainer.DataContainer.next().

def python.learner.folding.FoldingPolicy.FoldingPolicy.createFoldsets (   self,
  dataContainer,
  validationIndeces 
)

Create fold new data set Brings points given by validationIndeces together as test subset and the rest of points as train subset.

Parameters
dataContainerDataContainer with points
validationIndeceslist of indices for validation subset
Returns
: DataContainer partitioned data set

References python.learner.folding.FoldingPolicy.FoldingPolicy.seq, and sgpp::base::AbstractRefinement_refinement_key.seq.

def python.learner.folding.FoldingPolicy.FoldingPolicy.next (   self)

Implementation of iterator method next()

Returns
: the next subset

References python.learner.folding.FoldingPolicy.FoldingPolicy.dataFold, sgpp::combigrid::TensorGrid.level, sgpp::combigrid::ExponentialChebyshevPermutationIterator.level, sgpp::combigrid::ExponentialNoBoundaryPermutationIterator.level, sgpp::combigrid::ExponentialLevelorderPermutationIterator.level, python.learner.folding.FoldingPolicy.FoldingPolicy.level, sgpp::combigrid::AbstractEvaluator< V >.level, sgpp::combigrid::QueueEntry.level, python.learner.folding.FilesFoldingPolicy.FilesFoldingPolicy.level, and sgpp::base::HashGridPoint.level.

Referenced by python.learner.folding.FoldingPolicy.FoldingPolicy.__iter__().

Member Data Documentation

python.learner.folding.FoldingPolicy.FoldingPolicy.dataFold

List of partitioned data sets.

Referenced by python.learner.folding.FoldingPolicy.FoldingPolicy.next().

python.learner.folding.FoldingPolicy.FoldingPolicy.dataset

Dataset.

python.learner.folding.FoldingPolicy.FoldingPolicy.seq

Sequence of indices of points from data set.

Referenced by python.learner.folding.FoldingPolicy.FoldingPolicy.createFoldsets().

python.learner.folding.FoldingPolicy.FoldingPolicy.size

Size of dataset.

python.learner.folding.FoldingPolicy.FoldingPolicy.window

Number of points in one subset.


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