30 #ifndef MLPACK_METHODS_APPROX_KFN_DRUSILLA_SELECT_HPP 31 #define MLPACK_METHODS_APPROX_KFN_DRUSILLA_SELECT_HPP 38 template<
typename MatType = arma::mat>
73 void Train(
const MatType& referenceSet,
91 void Search(
const MatType& querySet,
93 arma::Mat<size_t>& neighbors,
94 arma::mat& distances);
99 template<
typename Archive>
100 void serialize(Archive& ar,
const uint32_t );
114 MatType candidateSet;
116 arma::Col<size_t> candidateIndices;
128 #include "drusilla_select_impl.hpp" void Train(const MatType &referenceSet, const size_t l=0, const size_t m=0)
Build the set of candidate points on the given reference set.
const MatType & CandidateSet() const
Access the candidate set.
Linear algebra utility functions, generally performed on matrices or vectors.
arma::Col< size_t > & CandidateIndices()
Modify the indices of points in the candidate set. Be careful!
The core includes that mlpack expects; standard C++ includes and Armadillo.
void serialize(Archive &ar, const uint32_t)
Serialize the model.
const arma::Col< size_t > & CandidateIndices() const
Access the indices of points in the candidate set.
void Search(const MatType &querySet, const size_t k, arma::Mat< size_t > &neighbors, arma::mat &distances)
Search for the k furthest neighbors of the given query set.
MatType & CandidateSet()
Modify the candidate set. Be careful!
DrusillaSelect(const MatType &referenceSet, const size_t l, const size_t m)
Construct the DrusillaSelect object with the given reference set (this is the set that will be search...