/usr/include/shogun/machine/DistanceMachine.h is in libshogun-dev 3.2.0-7.3build4.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 | /*
* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 3 of the License, or
* (at your option) any later version.
*
* Written (W) 2006-2009 Christian Gehl
* Written (W) 2006-2009 Soeren Sonnenburg
* Copyright (C) 1999-2009 Fraunhofer Institute FIRST and Max-Planck-Society
*/
#ifndef _DISTANCE_MACHINE_H__
#define _DISTANCE_MACHINE_H__
#include <shogun/lib/common.h>
#include <shogun/distance/Distance.h>
#include <shogun/labels/Labels.h>
#include <shogun/labels/RegressionLabels.h>
#include <shogun/machine/Machine.h>
#include <stdio.h>
namespace shogun
{
class CLabels;
class CRegressionLabels;
class CDistance;
class CMachine;
/** @brief A generic DistanceMachine interface.
*
* A distance machine is based on a a-priori choosen distance.
*/
class CDistanceMachine : public CMachine
{
public:
/** default constructor */
CDistanceMachine();
/** destructor */
virtual ~CDistanceMachine();
/** set distance
*
* @param d distance to set
*/
void set_distance(CDistance* d);
/** get distance
*
* @return distance
*/
CDistance* get_distance() const;
/**
* get distance functions for lhs feature vectors
* going from a1 to a2 and rhs feature vector b
*
* @param result array of distance values
* @param idx_a1 first feature vector a1 at idx_a1
* @param idx_a2 last feature vector a2 at idx_a2
* @param idx_b feature vector b at idx_b
*/
void distances_lhs(float64_t* result,int32_t idx_a1,int32_t idx_a2,int32_t idx_b);
/**
* get distance functions for rhs feature vectors
* going from b1 to b2 and lhs feature vector a
*
* @param result array of distance values
* @param idx_b1 first feature vector a1 at idx_b1
* @param idx_b2 last feature vector a2 at idx_b2
* @param idx_a feature vector a at idx_a
*/
void distances_rhs(float64_t* result,int32_t idx_b1,int32_t idx_b2,int32_t idx_a);
/** Returns the name of the SGSerializable instance. It MUST BE
* the CLASS NAME without the prefixed `C'.
*
* @return name of the SGSerializable
*/
virtual const char* get_name() const { return "DistanceMachine"; }
/** Classify all provided features.
* Cluster index with smallest distance to to be classified element is
* returned
*
* @param data (test)data to be classified
* @return classified labels
*/
virtual CMulticlassLabels* apply_multiclass(CFeatures* data=NULL);
/** Apply machine to one example.
* Cluster index with smallest distance to to be classified element is
* returned
*
* @param num which example to apply machine to
* @return cluster label nearest to example
*/
virtual float64_t apply_one(int32_t num);
protected:
/** Ensures cluster centers are in lhs of underlying distance
*
* NOT IMPLEMENTED!
* Base method. Is called automatically after train because flag is
* always true for distance machines.
* Since every distance machine has to make sure that
* cluster centers are in lhs of distance variable, it is unimplemented
* here and HAS to be implemented in subclasses.
*/
virtual void store_model_features();
/**
* thread function for computing distance values
*
* @param p thread parameter
*/
static void* run_distance_thread_lhs(void* p);
/**
* thread function for computing distance values
*
* @param p thread parameter
*/
static void* run_distance_thread_rhs(void* p);
private:
void init();
protected:
/** the distance */
CDistance* distance;
};
}
#endif
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