File instance_sampling.hpp¶

class IInstanceSampling¶

#include <instance_sampling.hpp>

Defines an interface for all classes that implement a method for sampling training examples.

Public Functions

inline virtual ~IInstanceSampling()¶

virtual const IWeightVector &sample() = 0¶

Creates and returns a sample of the available training examples.

Returns:: A reference to an object of type IWeightVector that provides access to the weights of the training examples in the sample

class IClassificationInstanceSamplingFactory¶

#include <instance_sampling.hpp>

Defines an interface for all factories that allow to create instances of the type IInstanceSampling that can be used in classification problems.

Public Functions

inline virtual ~IClassificationInstanceSamplingFactory()¶

virtual std::unique_ptr<IInstanceSampling> create(const CContiguousView<const uint8> &labelMatrix, const SinglePartition &partition, IStatistics &statistics, const EqualWeightVector &exampleWeights) const = 0¶

Creates and returns a new object of type IInstanceSampling.

Parameters:

labelMatrix – A reference to an object of type CContiguousView that provides access to the labels of the training examples
partition – A reference to an object of type SinglePartition that provides access to the indices of the training examples that are included in the training set
statistics – A reference to an object of type IStatistics that provides access to the statistics which serve as a basis for learning rules
exampleWeights – A reference to an object of type EqualWeightVector that provides access to the weights of individual training examples

Returns:

An unique pointer to an object of type IInstanceSampling that has been created

Creates and returns a new object of type IInstanceSampling.

Parameters:

labelMatrix – A reference to an object of type CContiguousView that provides access to the labels of the training examples
partition – A reference to an object of type SinglePartition that provides access to the indices of the training examples that are included in the training set
statistics – A reference to an object of type IStatistics that provides access to the statistics which serve as a basis for learning rules
exampleWeights – A reference to an object of type DenseWeightVector<float32> that provides access to the weights of individual training examples

Returns:

An unique pointer to an object of type IInstanceSampling that has been created

virtual std::unique_ptr<IInstanceSampling> create(const CContiguousView<const uint8> &labelMatrix, BiPartition &partition, IStatistics &statistics, const EqualWeightVector &exampleWeights) const = 0¶

Creates and returns a new object of type IInstanceSampling.

Parameters:

labelMatrix – A reference to an object of type CContiguousView that provides access to the labels of the training examples
partition – A reference to an object of type BiPartition that provides access to the indices of the training examples that are included in the training set and the holdout set, respectively
statistics – A reference to an object of type IStatistics that provides access to the statistics which serve as a basis for learning rules
exampleWeights – A reference to an object of type EqualWeightVector that provides access to the weights of individual training examples

Returns:

An unique pointer to an object of type IInstanceSampling that has been created

virtual std::unique_ptr<IInstanceSampling> create(const CContiguousView<const uint8> &labelMatrix, BiPartition &partition, IStatistics &statistics, const DenseWeightVector<float32> &exampleWeights) const = 0¶

Creates and returns a new object of type IInstanceSampling.

Parameters:

labelMatrix – A reference to an object of type CContiguousView that provides access to the labels of the training examples
partition – A reference to an object of type BiPartition that provides access to the indices of the training examples that are included in the training set and the holdout set, respectively
statistics – A reference to an object of type IStatistics that provides access to the statistics which serve as a basis for learning rules
exampleWeights – A reference to an object of type DenseWeightVector<float32> that provides access to the weights of individual training examples

Returns:

An unique pointer to an object of type IInstanceSampling that has been created

virtual std::unique_ptr<IInstanceSampling> create(const BinaryCsrView &labelMatrix, const SinglePartition &partition, IStatistics &statistics, const EqualWeightVector &exampleWeights) const = 0¶

Creates and returns a new object of type IInstanceSampling.

Parameters:

labelMatrix – A reference to an object of type BinaryCsrView that provides access to the labels of the training examples
partition – A reference to an object of type SinglePartition that provides access to the indices of the training examples that are included in the training set
statistics – A reference to an object of type IStatistics that provides access to the statistics which serve as a basis for learning rules
exampleWeights – A reference to an object of type EqualWeightVector that provides access to the weights of individual training examples

Returns:

An unique pointer to an object of type IInstanceSampling that has been created

virtual std::unique_ptr<IInstanceSampling> create(const BinaryCsrView &labelMatrix, const SinglePartition &partition, IStatistics &statistics, const DenseWeightVector<float32> &exampleWeights) const = 0¶

Creates and returns a new object of type IInstanceSampling.

Parameters:

labelMatrix – A reference to an object of type BinaryCsrView that provides access to the labels of the training examples
partition – A reference to an object of type SinglePartition that provides access to the indices of the training examples that are included in the training set
statistics – A reference to an object of type IStatistics that provides access to the statistics which serve as a basis for learning rules
exampleWeights – A reference to an object of type DenseWeightVector<float32> that provides access to the weights of individual training examples

Returns:

An unique pointer to an object of type IInstanceSampling that has been created

virtual std::unique_ptr<IInstanceSampling> create(const BinaryCsrView &labelMatrix, BiPartition &partition, IStatistics &statistics, const EqualWeightVector &exampleWeights) const = 0¶

Creates and returns a new object of type IInstanceSampling.

Parameters:

labelMatrix – A reference to an object of type BinaryCsrView that provides access to the labels of the training examples
partition – A reference to an object of type BiPartition that provides access to the indices of the training examples that are included in the training set and the holdout set, respectively
statistics – A reference to an object of type IStatistics that provides access to the statistics which serve as a basis for learning rules
exampleWeights – A reference to an object of type EqualWeightVector that provides access to the weights of individual training examples

Returns:

An unique pointer to an object of type IInstanceSampling that has been created

virtual std::unique_ptr<IInstanceSampling> create(const BinaryCsrView &labelMatrix, BiPartition &partition, IStatistics &statistics, const DenseWeightVector<float32> &exampleWeights) const = 0¶

Creates and returns a new object of type IInstanceSampling.

Parameters:

labelMatrix – A reference to an object of type BinaryCsrView that provides access to the labels of the training examples
partition – A reference to an object of type BiPartition that provides access to the indices of the training examples that are included in the training set and the holdout set, respectively
statistics – A reference to an object of type IStatistics that provides access to the statistics which serve as a basis for learning rules
exampleWeights – A reference to an object of type DenseWeightVector<float32> that provides access to the weights of individual training examples

Returns:

An unique pointer to an object of type IInstanceSampling that has been created

class IRegressionInstanceSamplingFactory¶

#include <instance_sampling.hpp>

Defines an interface for all factories that allow to create instances of the type IInstanceSampling that can be used in regression problems.

Public Functions

inline virtual ~IRegressionInstanceSamplingFactory()¶

virtual std::unique_ptr<IInstanceSampling> create(const CContiguousView<const float32> &regressionMatrix, const SinglePartition &partition, IStatistics &statistics, const EqualWeightVector &exampleWeights) const = 0¶

Creates and returns a new object of type IInstanceSampling.

Parameters:

regressionMatrix – A reference to an object of type CContiguousView that provides access to the regression scores of the training examples
partition – A reference to an object of type SinglePartition that provides access to the indices of the training examples that are included in the training set
statistics – A reference to an object of type IStatistics that provides access to the statistics which serve as a basis for learning rules
exampleWeights – A reference to an object of type EqualWeightVector that provides access to the weights of individual training examples

Returns:

An unique pointer to an object of type IInstanceSampling that has been created

Creates and returns a new object of type IInstanceSampling.

Parameters:

regressionMatrix – A reference to an object of type CContiguousView that provides access to the regression scores of the training examples
partition – A reference to an object of type SinglePartition that provides access to the indices of the training examples that are included in the training set
statistics – A reference to an object of type IStatistics that provides access to the statistics which serve as a basis for learning rules
exampleWeights – A reference to an object of type DenseWeightVector<float32> that provides access to the weights of individual training examples

Returns:

An unique pointer to an object of type IInstanceSampling that has been created

virtual std::unique_ptr<IInstanceSampling> create(const CContiguousView<const float32> &regressionMatrix, BiPartition &partition, IStatistics &statistics, const EqualWeightVector &exampleWeights) const = 0¶

Creates and returns a new object of type IInstanceSampling.

Parameters:

regressionMatrix – A reference to an object of type CContiguousView that provides access to the regression scores of the training examples
partition – A reference to an object of type BiPartition that provides access to the indices of the training examples that are included in the training set and the holdout set, respectively
statistics – A reference to an object of type IStatistics that provides access to the statistics which serve as a basis for learning rules
exampleWeights – A reference to an object of type EqualWeightVector that provides access to the weights of individual training examples

Returns:

An unique pointer to an object of type IInstanceSampling that has been created

Creates and returns a new object of type IInstanceSampling.

Parameters:

regressionMatrix – A reference to an object of type CContiguousView that provides access to the regression scores of the training examples
partition – A reference to an object of type BiPartition that provides access to the indices of the training examples that are included in the training set and the holdout set, respectively
statistics – A reference to an object of type IStatistics that provides access to the statistics which serve as a basis for learning rules
exampleWeights – A reference to an object of type DenseWeightVector<float32> that provides access to the weights of individual training examples

Returns:

An unique pointer to an object of type IInstanceSampling that has been created

virtual std::unique_ptr<IInstanceSampling> create(const CsrView<const float32> &regressionMatrix, const SinglePartition &partition, IStatistics &statistics, const EqualWeightVector &exampleWeights) const = 0¶

Creates and returns a new object of type IInstanceSampling.

Parameters:

regressionMatrix – A reference to an object of type CsrView that provides access to the regression scores of the training examples
partition – A reference to an object of type SinglePartition that provides access to the indices of the training examples that are included in the training set
statistics – A reference to an object of type IStatistics that provides access to the statistics which serve as a basis for learning rules
exampleWeights – A reference to an object of type EqualWeightVector that provides access to the weights of individual training examples

Returns:

An unique pointer to an object of type IInstanceSampling that has been created

Creates and returns a new object of type IInstanceSampling.

Parameters:

regressionMatrix – A reference to an object of type CsrView that provides access to the regression scores of the training examples
partition – A reference to an object of type SinglePartition that provides access to the indices of the training examples that are included in the training set
statistics – A reference to an object of type IStatistics that provides access to the statistics which serve as a basis for learning rules
exampleWeights – A reference to an object of type DenseWeightVector<float32> that provides access to the weights of individual training examples

Returns:

An unique pointer to an object of type IInstanceSampling that has been created

virtual std::unique_ptr<IInstanceSampling> create(const CsrView<const float32> &regressionMatrix, BiPartition &partition, IStatistics &statistics, const EqualWeightVector &exampleWeights) const = 0¶

Creates and returns a new object of type IInstanceSampling.

Parameters:

regressionMatrix – A reference to an object of type CsrView that provides access to the regression scores of the training examples
partition – A reference to an object of type BiPartition that provides access to the indices of the training examples that are included in the training set and the holdout set, respectively
statistics – A reference to an object of type IStatistics that provides access to the statistics which serve as a basis for learning rules
exampleWeights – A reference to an object of type EqualWeightVector that provides access to the weights of individual training examples

Returns:

An unique pointer to an object of type IInstanceSampling that has been created

virtual std::unique_ptr<IInstanceSampling> create(const CsrView<const float32> &regressionMatrix, BiPartition &partition, IStatistics &statistics, const DenseWeightVector<float32> &exampleWeights) const = 0¶

Creates and returns a new object of type IInstanceSampling.

Parameters:

regressionMatrix – A reference to an object of type CsrView that provides access to the regression scores of the training examples
partition – A reference to an object of type BiPartition that provides access to the indices of the training examples that are included in the training set and the holdout set, respectively
statistics – A reference to an object of type IStatistics that provides access to the statistics which serve as a basis for learning rules
exampleWeights – A reference to an object of type DenseWeightVector<float32> that provides access to the weights of individual training examples

Returns:

An unique pointer to an object of type IInstanceSampling that has been created

class IClassificationInstanceSamplingConfig¶

#include <instance_sampling.hpp>

Defines an interface for all classes that allow to configure a method for sampling instances that can be used in classification problems.

Subclassed by ExampleWiseStratifiedInstanceSamplingConfig, InstanceSamplingWithReplacementConfig, InstanceSamplingWithoutReplacementConfig, NoInstanceSamplingConfig, OutputWiseStratifiedInstanceSamplingConfig

Public Functions

inline virtual ~IClassificationInstanceSamplingConfig()¶

virtual std::unique_ptr<IClassificationInstanceSamplingFactory> createClassificationInstanceSamplingFactory() const = 0¶

Creates and returns a new object of type IClassificationInstanceSamplingFactory according to the specified configuration.

Returns:: An unique pointer to an object of type IClassificationInstanceSamplingFactory that has been created

class IRegressionInstanceSamplingConfig¶

#include <instance_sampling.hpp>

Defines an interface for all classes that allow to configure a method for sampling instances that can be used in regression problems.

Subclassed by InstanceSamplingWithReplacementConfig, InstanceSamplingWithoutReplacementConfig, NoInstanceSamplingConfig

Public Functions

inline virtual ~IRegressionInstanceSamplingConfig()¶

virtual std::unique_ptr<IRegressionInstanceSamplingFactory> createRegressionInstanceSamplingFactory() const = 0¶

Creates and returns a new object of type IRegressionInstanceSamplingFactory according to the specified configuration.

Returns:: An unique pointer to an object of type IRegressionInstanceSamplingFactory that has been created