valid/Validation.hpp File Reference

#include "ufjfmltk/classifier/Classifier.hpp"
#include "ufjfmltk/classifier/PrimalClassifier.hpp"
#include "ufjfmltk/classifier/DualClassifier.hpp"
#include "ufjfmltk/core/Data.hpp"
#include "ufjfmltk/core/Solution.hpp"

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Classes
struct	mltk::validation::ValidationReport
	Solution for the validation of a ML method. More...
struct	mltk::validation::CrossValidation
	Structure to manage cross validation. More...
struct	mltk::validation::TrainTestPair< T >
	A struct representing a pair with training and test data. More...

Namespaces
	mltk
	UFJF-MLTK main namespace for core functionalities.
	mltk::validation
	Validation methods namespace.

Functions
template<typename T >
std::vector< std::vector< size_t > >	mltk::validation::generateConfusionMatrix (Data< T > &samples, Learner< T > &learner)
	Compute the confusion matrix for a given trained classifier. More...
template<typename T >
ValidationReport	mltk::validation::metricsReport (const Data< T > &data, const std::vector< std::vector< size_t > > &cfm, std::vector< int > positive_labels=std::vector< int >())
	Generates a report with classifiers metrics. More...
template<typename T , typename Classifier >
double	mltk::validation::accuracy (const Data< T > &data, Classifier &model, bool trained=true)
double	mltk::validation::confusionMatrixAccuracy (const std::vector< std::vector< size_t > > &conf_matrix)
	Compute the accuracy based on a confusion matrix. More...
ValidationReport	mltk::validation::classificationReport (const Point< int > &real, const Point< int > &predicted)
template<typename T >
std::vector< TrainTestPair< T > >	mltk::validation::kfoldsplit (Data< T > &samples, size_t folds=5, bool stratified=true, bool keepIndex=true, size_t seed=0)
	Split the data in k folds. More...
template<typename T >
std::vector< TrainTestPair< T > >	mltk::validation::kfoldsplit (Data< T > &samples, size_t folds, size_t qtde, bool stratified=true, bool keepIndex=true, size_t seed=0)
	Split the data in k folds multiplied by the number of executions. More...
template<typename T >
TrainTestPair< T >	mltk::validation::partTrainTest (Data< T > &data, size_t fold, bool stratified=true, bool keepIndex=true, size_t seed=0)
	Divide the samples in training and test set. More...
template<typename T >
ValidationReport	mltk::validation::kfold (Data< T > sample, classifier::Classifier< T > &classifier, size_t fold, bool stratified=true, size_t seed=0, int verbose=0)
	Executes k-fold stratified cross-validation. More...
template<typename T >
ValidationReport	mltk::validation::kkfold (Data< T > samples, classifier::Classifier< T > &classifier, size_t qtde, size_t fold, bool stratified=true, size_t seed=0, int verbose=0)
	Executes the validation with several executions of the k fold algorithm. More...

Detailed Description

Validation wrapper class

Author

Mateus Coutinho Marim