best_binary_numeric_split.hpp

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#ifndef MLPACK_METHODS_DECISION_TREE_BEST_BINARY_NUMERIC_SPLIT_HPP
#define MLPACK_METHODS_DECISION_TREE_BEST_BINARY_NUMERIC_SPLIT_HPP

#include <mlpack/prereqs.hpp>
#include "mse_gain.hpp"

#include <mlpack/core/util/sfinae_utility.hpp>

namespace mlpack {
namespace tree {

// This gives us a HasBinaryGains<T, U> type (where U is a function pointer)
// we can use with SFINAE to catch when a type has a BinaryGains(...) function.
HAS_MEM_FUNC(BinaryGains, HasBinaryGains);

// This struct will have `value` set to `true` if a BinaryGains() function of
// the right signature is detected.  We only check for BinaryGains(), and not
// BinaryScanInitialize() or BinaryStep(), because those two are template
// members functions and would make this check far more difficult.
//
// The unused UseWeights template parameter is necessary to ensure that the
// compiler thinks the result `value` depends on a parameter specific to the
// SplitIfBetter() function in BestBinaryNumericSplit().
template<typename T, bool /* UseWeights */>
struct HasOptimizedBinarySplitForms
{
  const static bool value = HasBinaryGains<T,
      std::tuple<double, double>(T::*)()>::value;
};

template<typename FitnessFunction>
class BestBinaryNumericSplit
{
 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);

  template<bool UseWeights, typename VecType, typename ResponsesType,
           typename WeightVecType>
  static typename std::enable_if<
      !HasOptimizedBinarySplitForms<FitnessFunction, UseWeights>::value,
      double>::type
  SplitIfBetter(
      const double bestGain,
      const VecType& data,
      const ResponsesType& responses,
      const WeightVecType& weights,
      const size_t minimumLeafSize,
      const double minimumGainSplit,
      double& splitInfo,
      AuxiliarySplitInfo& aux,
      FitnessFunction& fitnessFunction);

  template<bool UseWeights, typename VecType, typename ResponsesType,
          typename WeightVecType>
  static typename std::enable_if<
      HasOptimizedBinarySplitForms<FitnessFunction, UseWeights>::value,
      double>::type
  SplitIfBetter(
      const double bestGain,
      const VecType& data,
      const ResponsesType& responses,
      const WeightVecType& weights,
      const size_t minimumLeafSize,
      const double minimumGainSplit,
      double& splitInfo,
      AuxiliarySplitInfo& /* aux */,
      FitnessFunction& fitnessFunction);

  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 "best_binary_numeric_split_impl.hpp"

#endif