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cgal
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Add computation of precision and recall

This commit is contained in:
Simon Giraudot 2017-03-01 14:28:55 +01:00
parent 509bd5ec69
commit 552693c5c0
1 changed files with 53 additions and 0 deletions
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53
Classification/include/CGAL/Classification/Trainer.h
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@ -47,6 +47,8 @@ public:
private:
Classifier* m_classifier;
std::vector<std::vector<std::size_t> > m_training_sets;
std::vector<double> m_precision;
std::vector<double> m_recall;
public:
@ -362,6 +364,57 @@ public:
return Label_handle();
}
void compute_precision_recall ()
{
std::vector<std::size_t> true_positives (m_classifier->number_of_labels());
std::vector<std::size_t> false_positives (m_classifier->number_of_labels());
std::vector<std::size_t> false_negatives (m_classifier->number_of_labels());
for (std::size_t j = 0; j < m_classifier->number_of_labels(); ++ j)
{
for (std::size_t k = 0; k < m_training_sets[j].size(); ++ k)
{
std::size_t nb_class_best=0;
double val_class_best = (std::numeric_limits<double>::max)();
for(std::size_t l = 0; l < m_classifier->number_of_labels(); ++ l)
{
double value = m_classifier->classification_value (m_classifier->label(l),
m_training_sets[j][k]);
if(val_class_best > value)
{
val_class_best = value;
nb_class_best = l;
}
}
if (nb_class_best == j)
++ true_positives[j];
else
{
++ false_negatives[j];
for(std::size_t l = 0; l < m_classifier->number_of_labels(); ++ l)
if (nb_class_best == l)
++ false_positives[l];
}
}
}
m_precision.clear();
m_recall.clear();
for (std::size_t j = 0; j < m_classifier->number_of_labels(); ++ j)
{
m_precision.push_back (true_positives[j] / double(true_positives[j] + false_positives[j]));
m_recall.push_back (true_positives[j] / double(true_positives[j] + false_negatives[j]));
std::cerr << m_classifier->label(j)->name() << ": " << std::endl
<< " * precision = " << m_precision.back() << std::endl
<< " * recall = " << m_recall.back() << std::endl
<< " * F_1 = " << 2. * (m_precision.back() * m_recall.back()) / (m_precision.back() + m_recall.back()) << std::endl;
}
}
/// \endcond
private: