binary_numeric_split.hpp

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#ifndef MLPACK_METHODS_HOEFFDING_SPLIT_BINARY_NUMERIC_SPLIT_HPP
#define MLPACK_METHODS_HOEFFDING_SPLIT_BINARY_NUMERIC_SPLIT_HPP

#include "binary_numeric_split_info.hpp"

namespace mlpack {
namespace tree {

template<typename FitnessFunction,
         typename ObservationType = double>
class BinaryNumericSplit
{
 public:
  typedef BinaryNumericSplitInfo<ObservationType> SplitInfo;

  BinaryNumericSplit(const size_t numClasses = 0);

  BinaryNumericSplit(const size_t numClasses, const BinaryNumericSplit& other);

  void Train(ObservationType value, const size_t label);

  void EvaluateFitnessFunction(double& bestFitness,
                               double& secondBestFitness);

  // Return the number of children if this node were to split on this feature.
  size_t NumChildren() const { return 2; }

  void Split(arma::Col<size_t>& childMajorities, SplitInfo& splitInfo);

  size_t MajorityClass() const;
  double MajorityProbability() const;

  template<typename Archive>
  void serialize(Archive& ar, const uint32_t /* version */);

 private:
  std::multimap<ObservationType, size_t> sortedElements;
  arma::Col<size_t> classCounts;

  ObservationType bestSplit;
  bool isAccurate;
};

// Convenience typedef.
template<typename FitnessFunction>
using BinaryDoubleNumericSplit = BinaryNumericSplit<FitnessFunction, double>;

} // namespace tree
} // namespace mlpack

// Include implementation.
#include "binary_numeric_split_impl.hpp"

#endif