random_forest.hpp

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#ifndef MLPACK_METHODS_RANDOM_FOREST_RANDOM_FOREST_HPP
#define MLPACK_METHODS_RANDOM_FOREST_RANDOM_FOREST_HPP
 
#include <mlpack/methods/decision_tree/decision_tree.hpp>
#include <mlpack/methods/decision_tree/multiple_random_dimension_select.hpp>
#include "bootstrap.hpp"
 
namespace mlpack {
namespace tree {
 
template<typename FitnessFunction = GiniGain,
         typename DimensionSelectionType = MultipleRandomDimensionSelect,
         template<typename> class NumericSplitType = BestBinaryNumericSplit,
         template<typename> class CategoricalSplitType = AllCategoricalSplit,
         typename ElemType = double>
class RandomForest
{
 public:
  typedef DecisionTree<FitnessFunction, NumericSplitType, CategoricalSplitType,
      DimensionSelectionType, ElemType> DecisionTreeType;
 
  RandomForest() { }
 
  template<typename MatType>
  RandomForest(const MatType& dataset,
               const arma::Row<size_t>& labels,
               const size_t numClasses,
               const size_t numTrees = 20,
               const size_t minimumLeafSize = 1,
               const double minimumGainSplit = 1e-7,
               const size_t maximumDepth = 0,
               DimensionSelectionType dimensionSelector =
                   DimensionSelectionType());
 
  template<typename MatType>
  RandomForest(const MatType& dataset,
               const data::DatasetInfo& datasetInfo,
               const arma::Row<size_t>& labels,
               const size_t numClasses,
               const size_t numTrees = 20,
               const size_t minimumLeafSize = 1,
               const double minimumGainSplit = 1e-7,
               const size_t maximumDepth = 0,
               DimensionSelectionType dimensionSelector =
                   DimensionSelectionType());
 
  template<typename MatType>
  RandomForest(const MatType& dataset,
               const arma::Row<size_t>& labels,
               const size_t numClasses,
               const arma::rowvec& weights,
               const size_t numTrees = 20,
               const size_t minimumLeafSize = 1,
               const double minimumGainSplit = 1e-7,
               const size_t maximumDepth = 0,
               DimensionSelectionType dimensionSelector =
                   DimensionSelectionType());
 
  template<typename MatType>
  RandomForest(const MatType& dataset,
               const data::DatasetInfo& datasetInfo,
               const arma::Row<size_t>& labels,
               const size_t numClasses,
               const arma::rowvec& weights,
               const size_t numTrees = 20,
               const size_t minimumLeafSize = 1,
               const double minimumGainSplit = 1e-7,
               const size_t maximumDepth = 0,
               DimensionSelectionType dimensionSelector =
                   DimensionSelectionType());
 
  template<typename MatType>
  double Train(const MatType& data,
               const arma::Row<size_t>& labels,
               const size_t numClasses,
               const size_t numTrees = 20,
               const size_t minimumLeafSize = 1,
               const double minimumGainSplit = 1e-7,
               const size_t maximumDepth = 0,
               DimensionSelectionType dimensionSelector =
                   DimensionSelectionType());
 
  template<typename MatType>
  double Train(const MatType& data,
               const data::DatasetInfo& datasetInfo,
               const arma::Row<size_t>& labels,
               const size_t numClasses,
               const size_t numTrees = 20,
               const size_t minimumLeafSize = 1,
               const double minimumGainSplit = 1e-7,
               const size_t maximumDepth = 0,
               DimensionSelectionType dimensionSelector =
                   DimensionSelectionType());
 
  template<typename MatType>
  double Train(const MatType& data,
               const arma::Row<size_t>& labels,
               const size_t numClasses,
               const arma::rowvec& weights,
               const size_t numTrees = 20,
               const size_t minimumLeafSize = 1,
               const double minimumGainSplit = 1e-7,
               const size_t maximumDepth = 0,
               DimensionSelectionType dimensionSelector =
                   DimensionSelectionType());
 
  template<typename MatType>
  double Train(const MatType& data,
               const data::DatasetInfo& datasetInfo,
               const arma::Row<size_t>& labels,
               const size_t numClasses,
               const arma::rowvec& weights,
               const size_t numTrees = 20,
               const size_t minimumLeafSize = 1,
               const double minimumGainSplit = 1e-7,
               const size_t maximumDepth = 0,
               DimensionSelectionType dimensionSelector =
                   DimensionSelectionType());
 
  template<typename VecType>
  size_t Classify(const VecType& point) const;
 
  template<typename VecType>
  void Classify(const VecType& point,
                size_t& prediction,
                arma::vec& probabilities) const;
 
  template<typename MatType>
  void Classify(const MatType& data,
                arma::Row<size_t>& predictions) const;
 
  template<typename MatType>
  void Classify(const MatType& data,
                arma::Row<size_t>& predictions,
                arma::mat& probabilities) const;
 
  const DecisionTreeType& Tree(const size_t i) const { return trees[i]; }
  DecisionTreeType& Tree(const size_t i) { return trees[i]; }
 
  size_t NumTrees() const { return trees.size(); }
 
  template<typename Archive>
  void serialize(Archive& ar, const unsigned int /* version */);
 
 private:
  template<bool UseWeights, bool UseDatasetInfo, typename MatType>
  double Train(const MatType& data,
               const data::DatasetInfo& datasetInfo,
               const arma::Row<size_t>& labels,
               const size_t numClasses,
               const arma::rowvec& weights,
               const size_t numTrees,
               const size_t minimumLeafSize,
               const double minimumGainSplit,
               const size_t maximumDepth,
               DimensionSelectionType& dimensionSelector);
 
  std::vector<DecisionTreeType> trees;
};
 
} // namespace tree
} // namespace mlpack
 
// Include implementation.
#include "random_forest_impl.hpp"
 
#endif