Aakash-kaushik/mlpack/hilbert__r__tree__descent__heuristic_8hpp_source.html

 #ifndef MLPACK_CORE_TREE_RECTANGLE_TREE_HR_TREE_DESCENT_HEURISTIC_HPP
 #define MLPACK_CORE_TREE_RECTANGLE_TREE_HR_TREE_DESCENT_HEURISTIC_HPP

 #include <mlpack/prereqs.hpp>

 namespace mlpack {
 namespace tree {

 class HilbertRTreeDescentHeuristic
 {
  public:
   template<typename TreeType>
   static size_t ChooseDescentNode(const TreeType* node, const size_t point);

   template<typename TreeType>
   static size_t ChooseDescentNode(const TreeType* node,
                                   const TreeType* insertedNode);
 };

 } //  namespace tree
 } //  namespace mlpack

 #include "hilbert_r_tree_descent_heuristic_impl.hpp"

 #endif // MLPACK_CORE_TREE_RECTANGLE_TREE_HR_TREE_DESCENT_HEURISTIC_HPP
mlpack
Linear algebra utility functions, generally performed on matrices or vectors.
Definition: cv.hpp:1

prereqs.hpp
The core includes that mlpack expects; standard C++ includes and Armadillo.

hilbert_r_tree_descent_heuristic_impl.hpp

mlpack::tree::HilbertRTreeDescentHeuristic
This class chooses the best child of a node in a Hilbert R tree when inserting a new point...
Definition: hilbert_r_tree_descent_heuristic.hpp:26

mlpack::tree::HilbertRTreeDescentHeuristic::ChooseDescentNode
static size_t ChooseDescentNode(const TreeType *node, const size_t point)
Evaluate the node using a heuristic.
Definition: hilbert_r_tree_descent_heuristic_impl.hpp:22