log_multi.h File Reference

Go to the source code of this file.

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

Function Documentation

log_multi_setup()

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

Definition at line 496 of file log_multi.cc.

References add(), VW::config::options_i::add_and_parse(), LEARNER::as_singleline(), getLossFunction(), LEARNER::init_multiclass_learner(), init_tree(), learn(), vw::loss, LEARNER::make_base(), VW::config::make_option(), vw::p, predict(), save_load_tree(), setup_base(), and VW::config::options_i::was_supplied().

Referenced by parse_reductions().

{
  auto data = scoped_calloc_or_throw<log_multi>();
  option_group_definition new_options("Logarithmic Time Multiclass Tree");
  new_options.add(make_option("log_multi", data->k).keep().help("Use online tree for multiclass"))
      .add(make_option("no_progress", data->progress).help("disable progressive validation"))
      .add(make_option("swap_resistance", data->swap_resist).default_value(4).help("disable progressive validation"))
      .add(make_option("swap_resistance", data->swap_resist)
               .default_value(4)
               .help("higher = more resistance to swap, default=4"));
  options.add_and_parse(new_options);

  if (!options.was_supplied("log_multi"))
    return nullptr;

  data->progress = !data->progress;

  std::string loss_function = "quantile";
  float loss_parameter = 0.5;
  delete (all.loss);
  all.loss = getLossFunction(all, loss_function, loss_parameter);

  data->max_predictors = data->k - 1;
  init_tree(*data.get());

  learner<log_multi, example>& l = init_multiclass_learner(
      data, as_singleline(setup_base(options, all)), learn, predict, all.p, data->max_predictors);
  l.set_save_load(save_load_tree);

  return make_base(l);
}