AbstractNearestNeighbors.h
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1 //===========================================================================
2 /*!
3  *
4  *
5  * \brief Interface for nearest Neighbor queries
6  *
7  *
8  *
9  * \author O.Krause
10  * \date 2012-2014
11  *
12  *
13  * \par Copyright 1995-2017 Shark Development Team
14  *
15  * <BR><HR>
16  * This file is part of Shark.
17  * <http://shark-ml.org/>
18  *
19  * Shark is free software: you can redistribute it and/or modify
20  * it under the terms of the GNU Lesser General Public License as published
21  * by the Free Software Foundation, either version 3 of the License, or
22  * (at your option) any later version.
23  *
24  * Shark is distributed in the hope that it will be useful,
25  * but WITHOUT ANY WARRANTY; without even the implied warranty of
26  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
27  * GNU Lesser General Public License for more details.
28  *
29  * You should have received a copy of the GNU Lesser General Public License
30  * along with Shark. If not, see <http://www.gnu.org/licenses/>.
31  *
32  */
33 //===========================================================================
34 
35 #ifndef SHARK_ALGORITHMS_NEARESTNEIGHBORS_ABSTRACTNEARESTNEIGHBORS_H
36 #define SHARK_ALGORITHMS_NEARESTNEIGHBORS_ABSTRACTNEARESTNEIGHBORS_H
37 
39 #include <shark/Data/Dataset.h>
40 namespace shark{
41 
42 
43 /// \brief Interface for Nearest Neighbor queries.
44 ///
45 /// Defines the abstract interface for query of nearest neighbors. This is used to generalize over the different algorithms
46 /// to query for nearest neighbors.
47 template<class InputType,class LabelType>
49 public:
52 
53  ///\brief Returns the k-nearest neighbors of a batch of points and returns them as linearized array.
54  ///
55  ///Given a batch of size n, a array with nxk values is returned where each entry is a key-value pair of distance and label.
56  ///the first k entries are the neighbors of point 1, the next k of point 2 and so on.
57  virtual std::vector<DistancePair> getNeighbors(BatchInputType const& batch, std::size_t k) const = 0;
58 
59  /// \brief Returns the expected shape of the inputs
60  Shape const& inputShape() const{
61  return m_inputShape;
62  }
63 
64  ///\brief returns a const reference to the dataset used by the algorithm
65  virtual LabeledData<InputType,LabelType>const& dataset()const = 0;
66 
68 protected:
70 };
71 
72 
73 }
74 
75 #endif