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Added unit tests for svm_rank_trainer::force_last_weight_to_1()

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Davis King 2012-12-19 23:00:53 -05:00
parent 824eb4558d
commit 19c02d3862
1 changed files with 85 additions and 0 deletions
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85
dlib/test/ranking.cpp
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@ -222,6 +222,89 @@ namespace
}
// ----------------------------------------------------------------------------------------
template <typename K>
class simple_rank_trainer
{
public:
template <typename T>
decision_function<K> train (
const ranking_pair<T>& pair
) const
{
typedef matrix<double,10,1> sample_type;
std::vector<sample_type> relevant = pair.relevant;
std::vector<sample_type> nonrelevant = pair.nonrelevant;
std::vector<sample_type> samples;
std::vector<double> labels;
for (unsigned long i = 0; i < relevant.size(); ++i)
{
for (unsigned long j = 0; j < nonrelevant.size(); ++j)
{
samples.push_back(relevant[i] - nonrelevant[j]);
labels.push_back(+1);
samples.push_back(nonrelevant[i] - relevant[j]);
labels.push_back(-1);
}
}
svm_c_linear_dcd_trainer<K> trainer;
trainer.set_c(1.0/samples.size());
trainer.set_epsilon(1e-10);
trainer.force_last_weight_to_1(true);
//trainer.be_verbose();
return trainer.train(samples, labels);
}
};
void test_svmrank_weight_force_dense()
{
print_spinner();
typedef matrix<double,10,1> sample_type;
typedef linear_kernel<sample_type> kernel_type;
ranking_pair<sample_type> pair;
for (int i = 0; i < 20; ++i)
{
pair.relevant.push_back(abs(gaussian_randm(10,1,i)));
}
for (int i = 0; i < 20; ++i)
{
pair.nonrelevant.push_back(-abs(gaussian_randm(10,1,i+10000)));
pair.nonrelevant.back()(9) += 1;
}
svm_rank_trainer<kernel_type> trainer;
trainer.force_last_weight_to_1(true);
trainer.set_epsilon(1e-13);
//trainer.be_verbose();
decision_function<kernel_type> df;
df = trainer.train(pair);
dlog << LINFO << "weights: "<< trans(df.basis_vectors(0));
const double acc1 = test_ranking_function(df, pair);
dlog << LINFO << "ranking accuracy: " << acc1;
DLIB_TEST(std::abs(acc1 - 1) == 0);
simple_rank_trainer<kernel_type> strainer;
decision_function<kernel_type> df2;
df2 = strainer.train(pair);
dlog << LINFO << "weights: "<< trans(df2.basis_vectors(0));
const double acc2 = test_ranking_function(df2, pair);
dlog << LINFO << "ranking accuracy: " << acc2;
DLIB_TEST(std::abs(acc2 - 1) == 0);
dlog << LINFO << "w error: " << max(abs(df.basis_vectors(0) - df2.basis_vectors(0)));
dlog << LINFO << "b error: " << abs(df.b - df2.b);
DLIB_TEST(std::abs(max(abs(df.basis_vectors(0) - df2.basis_vectors(0)))) < 1e-8);
DLIB_TEST(std::abs(abs(df.b - df2.b)) < 1e-8);
}
// ----------------------------------------------------------------------------------------
// ----------------------------------------------------------------------------------------
// ----------------------------------------------------------------------------------------
@ -242,6 +325,8 @@ namespace
test_count_ranking_inversions();
dotest1();
dotest_sparse_vectors();
test_svmrank_weight_force_dense();
}
} a;