Solution for the validation of a ML method. More...

#include <Validation.hpp>

Inheritance diagram for mltk::validation::ValidationReport:

Collaboration diagram for mltk::validation::ValidationReport:

[legend]

Public Member Functions
void	print () const

Public Member Functions inherited from mltk::Solution
Solution &	operator= (const Solution &other)

Public Attributes
double	accuracy = 0.0
	Accuracy of the validated model. More...

double	error = 0.0

double	precision = 0.0
	Precision of the validated model. More...

double	recall = 0.0
	Recall of the validated model. More...

double	sensitivity {0.0}

double	specificity {0.0}

double	fscore {0.0}

size_t	errors {0}

size_t	tp {0}

size_t	tn {0}

size_t	fp {0}

size_t	fn {0}

double	tnrate = 0.0
	True negative rate. More...

double	tprate = 0.0
	True positive rate. More...

size_t	falsePositive = 0
	Number of false positives generated by the classifier in the evaluation. More...

size_t	falseNegative = 0
	Number of false negatives generated by the classifier in the evaluation. More...

size_t	trueNegative = 0
	Number of true negatives generated by the classifier in the evaluation. More...

size_t	truePositive = 0
	Number of true positives generated by the classifier in the evaluation. More...

Public Attributes inherited from mltk::Solution
mltk::Point< double >	w
	Weights vector. More...

mltk::Point< double >	func

Kernel< double >	K
	Kernel for Dual methods. More...

std::vector< double >	alpha
	Alpha Vector for Dual methods. More...

double	bias = 0
	Bias of the solution. More...

std::vector< int >	fnames
	Features names of the resulting solution. More...

double	margin = 0
	Margin generated from the classifier that generated the solution. More...

double	norm = 0
	Norm of the solution. More...

unsigned int	svs = 0
	Number of support Vectors. More...

Detailed Description

Solution for the validation of a ML method.

Member Data Documentation

◆ accuracy

double mltk::validation::ValidationReport::accuracy = 0.0

Accuracy of the validated model.

◆ falseNegative

size_t mltk::validation::ValidationReport::falseNegative = 0

Number of false negatives generated by the classifier in the evaluation.

◆ falsePositive

size_t mltk::validation::ValidationReport::falsePositive = 0

Number of false positives generated by the classifier in the evaluation.

◆ precision

double mltk::validation::ValidationReport::precision = 0.0

Precision of the validated model.

◆ recall

double mltk::validation::ValidationReport::recall = 0.0

Recall of the validated model.

◆ tnrate

double mltk::validation::ValidationReport::tnrate = 0.0

True negative rate.

◆ tprate

double mltk::validation::ValidationReport::tprate = 0.0

True positive rate.

◆ trueNegative

size_t mltk::validation::ValidationReport::trueNegative = 0

Number of true negatives generated by the classifier in the evaluation.

◆ truePositive

size_t mltk::validation::ValidationReport::truePositive = 0

Number of true positives generated by the classifier in the evaluation.

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

valid/Validation.hpp

Public Member Functions

Public Attributes