random_binary_numeric_split.hpp

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#ifndef MLPACK_METHODS_DECISION_TREE_RANDOM_BINARY_NUMERIC_SPLIT_HPP
#define MLPACK_METHODS_DECISION_TREE_RANDOM_BINARY_NUMERIC_SPLIT_HPP

#include <mlpack/prereqs.hpp>

namespace mlpack {
namespace tree {

template<typename FitnessFunction>
class RandomBinaryNumericSplit
{
 public:
  // No extra info needed for split.
  class AuxiliarySplitInfo { };

  template<bool UseWeights, typename VecType, typename WeightVecType>
  static double SplitIfBetter(
      const double bestGain,
      const VecType& data,
      const arma::Row<size_t>& labels,
      const size_t numClasses,
      const WeightVecType& weights,
      const size_t minimumLeafSize,
      const double minimumGainSplit,
      arma::vec& splitInfo,
      AuxiliarySplitInfo& aux,
      const bool splitIfBetterGain = false);

  template<bool UseWeights, typename VecType, typename WeightVecType>
  static double SplitIfBetter(
      const double bestGain,
      const VecType& data,
      const arma::rowvec& responses,
      const WeightVecType& weights,
      const size_t minimumLeafSize,
      const double minimumGainSplit,
      double& splitInfo,
      AuxiliarySplitInfo& aux,
      const bool splitIfBetterGain = false);

  static size_t NumChildren(const double& /* splitInfo */,
                            const AuxiliarySplitInfo& /* aux */)
  {
    return 2;
  }

  template<typename ElemType>
  static size_t CalculateDirection(
      const ElemType& point,
      const double& splitInfo,
      const AuxiliarySplitInfo& /* aux */);
};

} // namespace tree
} // namespace mlpack

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

#endif