File loss_decomposable_squared_error.hpp¶

namespace boosting

#include <loss_decomposable_squared_error.hpp>

Allows to configure a loss function that implements a multivariate variant of the squared error loss that is decomposable.

Public Functions

DecomposableSquaredErrorLossConfig(ReadableProperty<IHeadConfig> headConfig)¶

Parameters:: headConfig – A ReadableProperty that allows to access the IHeadConfig that stores the configuration of rule heads

virtual std::unique_ptr<IClassificationStatisticsProviderFactory> createClassificationStatisticsProviderFactory(const IFeatureMatrix &featureMatrix, const IRowWiseLabelMatrix &labelMatrix, const Blas &blas, const Lapack &lapack, bool preferSparseStatistics) const override¶

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

Parameters:

featureMatrix – A reference to an object of type IFeatureMatrix that provides access to the feature values of the training examples
labelMatrix – A reference to an object of type IRowWiseLabelMatrix that provides access to the labels of the training examples
blas – A reference to an object of type Blas that allows to execute BLAS routines
lapack – A reference to an object of type Lapack that allows to execute LAPACK routines
preferSparseStatistics – True, if a sparse representation of statistics should be preferred, if possible, false otherwise

Returns:

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

virtual std::unique_ptr<IRegressionStatisticsProviderFactory> createRegressionStatisticsProviderFactory(const IFeatureMatrix &featureMatrix, const IRowWiseRegressionMatrix &regressionMatrix, const Blas &blas, const Lapack &lapack, bool preferSparseStatistics) const override¶

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

Parameters:

featureMatrix – A reference to an object of type IFeatureMatrix that provides access to the feature values of the training examples
regressionMatrix – A reference to an object of type IRowWiseRegressionMatrix that provides access to the regression scores of the training examples
blas – A reference to an object of type Blas that allows to execute BLAS routines
lapack – A reference to an object of type Lapack that allows to execute LAPACK routines
preferSparseStatistics – True, if a sparse representation of statistics should be preferred, if possible, false otherwise

Returns:

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

virtual std::unique_ptr<IMarginalProbabilityFunctionFactory> createMarginalProbabilityFunctionFactory() const override¶

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

Returns:: An unique pointer to an object of type IMarginalProbabilityFunctionFactory that has been created or a null pointer, if the loss function does not support the prediction of marginal probabilities

virtual std::unique_ptr<IJointProbabilityFunctionFactory> createJointProbabilityFunctionFactory() const override¶

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

Returns:: An unique pointer to an object of type IJointProbabilityFunctionFactory that has been created to a null pointer, if the loss function does not support the prediction of joint probabilities

virtual float64 getDefaultPrediction() const override¶

Returns the default prediction for an example that is not covered by any rules.

virtual std::unique_ptr<IDecomposableClassificationLossFactory> createDecomposableClassificationLossFactory() const override¶

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

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

virtual std::unique_ptr<IDecomposableRegressionLossFactory> createDecomposableRegressionLossFactory() const override¶

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

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

Private Members