K2_tpl.h

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#include <type_traits>

#include <agrum/learning/paramUtils/DAG2BNLearner.h>
#include <agrum/learning/structureUtils/graphChange.h>
#include <agrum/learning/structureUtils/graphChangesGenerator4K2.h>

namespace gum {

  namespace learning {

    template < typename GRAPH_CHANGES_SELECTOR >
    DAG K2::learnStructure(GRAPH_CHANGES_SELECTOR& selector, DAG initial_dag) {
      // check that we used a selector compatible with the K2 algorithm
      static_assert(
         std::is_base_of< __GraphChangesGenerator4K2,
                          typename GRAPH_CHANGES_SELECTOR::GeneratorType >::value,
         "K2 must be called with a K2-compliant Graph Change Generator");

      // check that the order passed in argument concerns all the nodes
      //__checkOrder(modal);

      // get the generator and assign the order
      auto& generator = selector.graphChangeGenerator();
      generator.setOrder(__order);

      // use the greedy hill climbing algorithm to perform the search
      return GreedyHillClimbing::learnStructure(selector, initial_dag);
    }

    template < typename GUM_SCALAR,
               typename GRAPH_CHANGES_SELECTOR,
               typename PARAM_ESTIMATOR >
    BayesNet< GUM_SCALAR > K2::learnBN(GRAPH_CHANGES_SELECTOR& selector,
                                       PARAM_ESTIMATOR&        estimator,
                                       DAG                     initial_dag) {
      // check that we used a selector compatible with the K2 algorithm
      static_assert(
         std::is_base_of< __GraphChangesGenerator4K2,
                          typename GRAPH_CHANGES_SELECTOR::GeneratorType >::value,
         "K2 must be called with a K2-compliant Graph Change Generator");

      // check that the order passed in argument concerns all the nodes
      //__checkOrder(modal);

      // get the generator and assign the order
      auto& generator = selector.graphChangeGenerator();
      generator.setOrder(__order);

      // use the greedy hill climbing algorithm to perform the search
      return GreedyHillClimbing::learnBN< GUM_SCALAR >(
         selector, estimator, initial_dag);
    }

  } /* namespace learning */

} /* namespace gum */