mlpack::cv::CVBase< MLAlgorithm, MatType, PredictionsType, WeightsType > Class Template Reference

An auxiliary class for cross-validation. More...

#include <cv_base.hpp>

Public Types
using	MIE = MetaInfoExtractor< MLAlgorithm, MatType, PredictionsType, WeightsType >
	A short alias for MetaInfoExtractor.

Public Member Functions
	CVBase ()
	Assert that MLAlgorithm doesn't take any additional basic parameters like numClasses.
	CVBase (const size_t numClasses)
	Assert that MLAlgorithm takes the numClasses parameter and store it. More...
	CVBase (const data::DatasetInfo &datasetInfo, const size_t numClasses)
	Assert that MLAlgorithm takes the numClasses parameter and a data::DatasetInfo parameter and store them. More...
template<typename... MLAlgorithmArgs>
MLAlgorithm	Train (const MatType &xs, const PredictionsType &ys, const MLAlgorithmArgs &... args)
	Train MLAlgorithm with given data points, predictions, and hyperparameters depending on what CVBase constructor has been called.
template<typename... MLAlgorithmArgs>
MLAlgorithm	Train (const MatType &xs, const PredictionsType &ys, const WeightsType &weights, const MLAlgorithmArgs &... args)
	Train MLAlgorithm with given data points, predictions, weights, and hyperparameters depending on what CVBase constructor has been called.

Static Public Member Functions
static void	AssertDataConsistency (const MatType &xs, const PredictionsType &ys)
	Assert there is the equal number of data points and predictions.
static void	AssertWeightsConsistency (const MatType &xs, const WeightsType &weights)
	Assert weighted learning is supported and there is the equal number of data points and weights.

Detailed Description

template<typename MLAlgorithm, typename MatType, typename PredictionsType, typename WeightsType>
class mlpack::cv::CVBase< MLAlgorithm, MatType, PredictionsType, WeightsType >

An auxiliary class for cross-validation.

It serves to handle basic non-data constructor parameters of a machine learning algorithm (like datasetInfo or numClasses) and to assert that the machine learning algorithm and data satisfy certain conditions.

This class is not meant to be used directly by users. To cross-validate rather use end-user classes like SimpleCV or KFoldCV.

Template Parameters

MLAlgorithm	A machine learning algorithm.
MatType	The type of data.
PredictionsType	The type of predictions (labels/responses).
WeightsType	The type of weights. It supposed to be void* when weights are not supported.

Constructor & Destructor Documentation

CVBase() [1/2]

template<typename MLAlgorithm , typename MatType , typename PredictionsType , typename WeightsType >

mlpack::cv::CVBase< MLAlgorithm, MatType, PredictionsType, WeightsType >::CVBase

(

const size_t

numClasses

)

Assert that MLAlgorithm takes the numClasses parameter and store it.

Parameters

numClasses

Number of classes in the dataset.

CVBase() [2/2]

template<typename MLAlgorithm , typename MatType , typename PredictionsType , typename WeightsType >

mlpack::cv::CVBase< MLAlgorithm, MatType, PredictionsType, WeightsType >::CVBase	(	const data::DatasetInfo &	datasetInfo,
		const size_t	numClasses
	)

Assert that MLAlgorithm takes the numClasses parameter and a data::DatasetInfo parameter and store them.

Parameters

datasetInfo	Type information for each dimension of the dataset.
numClasses	Number of classes in the dataset.

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

• src/mlpack/core/cv/cv_base.hpp
• src/mlpack/core/cv/cv_base_impl.hpp