confidence.h File Reference

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Functions
LEARNER::base_learner *	confidence_setup (VW::config::options_i &options, vw &all)

Function Documentation

confidence_setup()

LEARNER::base_learner* confidence_setup	(	VW::config::options_i &	options,
		vw &	all
	)

Definition at line 86 of file confidence.cc.

References VW::config::option_group_definition::add(), VW::config::options_i::add_and_parse(), LEARNER::as_singleline(), LEARNER::init_learner(), LEARNER::make_base(), VW::config::make_option(), return_confidence_example(), LEARNER::learner< T, E >::set_finish_example(), setup_base(), and vw::training.

Referenced by parse_reductions().

{
  bool confidence_arg = false;
  bool confidence_after_training = false;
  option_group_definition new_options("Confidence");
  new_options.add(make_option("confidence", confidence_arg).keep().help("Get confidence for binary predictions"))
      .add(make_option("confidence_after_training", confidence_after_training).help("Confidence after training"));
  options.add_and_parse(new_options);

  if (!confidence_arg)
    return nullptr;

  if (!all.training)
  {
    std::cout
        << "Confidence does not work in test mode because learning algorithm state is needed.  Use --save_resume when "
           "saving the model and avoid --test_only"
        << std::endl;
    return nullptr;
  }

  auto data = scoped_calloc_or_throw<confidence>();
  data->all = &all;

  void (*learn_with_confidence_ptr)(confidence&, single_learner&, example&) = nullptr;
  void (*predict_with_confidence_ptr)(confidence&, single_learner&, example&) = nullptr;

  if (confidence_after_training)
  {
    learn_with_confidence_ptr = predict_or_learn_with_confidence<true, true>;
    predict_with_confidence_ptr = predict_or_learn_with_confidence<false, true>;
  }
  else
  {
    learn_with_confidence_ptr = predict_or_learn_with_confidence<true, false>;
    predict_with_confidence_ptr = predict_or_learn_with_confidence<false, false>;
  }

  // Create new learner
  learner<confidence, example>& l = init_learner(
      data, as_singleline(setup_base(options, all)), learn_with_confidence_ptr, predict_with_confidence_ptr);

  l.set_finish_example(return_confidence_example);

  return make_base(l);
}