14 using namespace shark;
23 void draw(RealVector& input,
unsigned int& label)
const 25 label = Rng::discrete(0, 4);
27 input(0) = Rng::gauss() + 3.0 * label;
34 std::cout <<
"kernel logistic regression example program" << std::endl;
37 unsigned int ell = 1000;
38 unsigned int tests = 1000;
61 trainer.
train(classifier, training);
65 double train_error = loss.
eval(training.
labels(), output);
66 std::cout <<
"training error: " << train_error << std::endl;
67 output = classifier(test.
inputs());
68 double test_error = loss.
eval(test.
labels(), output);
69 std::cout <<
" test error: " << test_error << std::endl;