fastmks.hpp
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1 
13 #ifndef MLPACK_METHODS_FASTMKS_FASTMKS_HPP
14 #define MLPACK_METHODS_FASTMKS_FASTMKS_HPP
15 
16 #include <mlpack/prereqs.hpp>
18 #include "fastmks_stat.hpp"
20 #include <queue>
21 
22 namespace mlpack {
23 namespace fastmks {
24 
56 template<
57  typename KernelType,
58  typename MatType = arma::mat,
59  template<typename TreeMetricType,
60  typename TreeStatType,
61  typename TreeMatType> class TreeType = tree::StandardCoverTree
62 >
63 class FastMKS
64 {
65  public:
67  typedef TreeType<metric::IPMetric<KernelType>, FastMKSStat, MatType> Tree;
68 
76  FastMKS(const bool singleMode = false, const bool naive = false);
77 
87  FastMKS(const MatType& referenceSet,
88  const bool singleMode = false,
89  const bool naive = false);
90 
102  FastMKS(const MatType& referenceSet,
103  KernelType& kernel,
104  const bool singleMode = false,
105  const bool naive = false);
106 
117  FastMKS(MatType&& referenceSet,
118  const bool singleMode = false,
119  const bool naive = false);
120 
133  FastMKS(MatType&& referenceSet,
134  KernelType& kernel,
135  const bool singleMode = false,
136  const bool naive = false);
137 
149  FastMKS(Tree* referenceTree,
150  const bool singleMode = false);
151 
155  FastMKS(const FastMKS& other);
156 
160  FastMKS(FastMKS&& other);
161 
165  FastMKS& operator=(const FastMKS& other);
166 
168  ~FastMKS();
169 
176  void Train(const MatType& referenceSet);
177 
186  void Train(const MatType& referenceSet, KernelType& kernel);
187 
195  void Train(MatType&& referenceSet);
196 
205  void Train(MatType&& referenceSet, KernelType& kernel);
206 
214  void Train(Tree* referenceTree);
215 
236  void Search(const MatType& querySet,
237  const size_t k,
238  arma::Mat<size_t>& indices,
239  arma::mat& kernels);
240 
263  void Search(Tree* querySet,
264  const size_t k,
265  arma::Mat<size_t>& indices,
266  arma::mat& kernels);
267 
282  void Search(const size_t k,
283  arma::Mat<size_t>& indices,
284  arma::mat& products);
285 
287  const metric::IPMetric<KernelType>& Metric() const { return metric; }
289  metric::IPMetric<KernelType>& Metric() { return metric; }
290 
292  bool SingleMode() const { return singleMode; }
294  bool& SingleMode() { return singleMode; }
295 
297  bool Naive() const { return naive; }
299  bool& Naive() { return naive; }
300 
302  template<typename Archive>
303  void serialize(Archive& ar, const unsigned int /* version */);
304 
305  private:
308  const MatType* referenceSet;
310  Tree* referenceTree;
312  bool treeOwner;
314  bool setOwner;
315 
317  bool singleMode;
319  bool naive;
320 
323 
325  typedef std::pair<double, size_t> Candidate;
326 
328  struct CandidateCmp {
329  bool operator()(const Candidate& c1, const Candidate& c2)
330  {
331  return c1.first > c2.first;
332  };
333  };
334 
336  typedef std::priority_queue<Candidate, std::vector<Candidate>,
337  CandidateCmp> CandidateList;
338 };
339 
340 } // namespace fastmks
341 } // namespace mlpack
342 
343 // Include implementation.
344 #include "fastmks_impl.hpp"
345 
346 #endif
bool SingleMode() const
Get whether or not single-tree search is used.
Definition: fastmks.hpp:292
const metric::IPMetric< KernelType > & Metric() const
Get the inner-product metric induced by the given kernel.
Definition: fastmks.hpp:287
strip_type.hpp
Definition: add_to_po.hpp:21
The core includes that mlpack expects; standard C++ includes and Armadillo.
bool & Naive()
Modify whether or not brute-force (naive) search is used.
Definition: fastmks.hpp:299
The inner product metric, IPMetric, takes a given Mercer kernel (KernelType), and when Evaluate() is ...
Definition: ip_metric.hpp:32
FastMKS(const bool singleMode=false, const bool naive=false)
Create the FastMKS object with an empty reference set and default kernel.
~FastMKS()
Destructor for the FastMKS object.
metric::IPMetric< KernelType > & Metric()
Modify the inner-product metric induced by the given kernel.
Definition: fastmks.hpp:289
bool & SingleMode()
Modify whether or not single-tree search is used.
Definition: fastmks.hpp:294
bool Naive() const
Get whether or not brute-force (naive) search is used.
Definition: fastmks.hpp:297
TreeType< metric::IPMetric< KernelType >, FastMKSStat, MatType > Tree
Convenience typedef.
Definition: fastmks.hpp:67
void Search(const MatType &querySet, const size_t k, arma::Mat< size_t > &indices, arma::mat &kernels)
Search for the points in the reference set with maximum kernel evaluation to each point in the given ...
The statistic used in trees with FastMKS.
void Train(const MatType &referenceSet)
"Train" the FastMKS model on the given reference set (this will just build a tree, if the current search mode is not naive mode).
FastMKS & operator=(const FastMKS &other)
Assign this model to be a copy of the given model.
An implementation of fast exact max-kernel search.
Definition: fastmks.hpp:63
A cover tree is a tree specifically designed to speed up nearest-neighbor computation in high-dimensi...
Definition: cover_tree.hpp:99
void serialize(Archive &ar, const unsigned int)
Serialize the model.