/usr/include/shogun/classifier/NearestCentroid.h is in libshogun-dev 3.2.0-7.3build4.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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 | /*
* 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) 2012 Philippe Tillet
*/
#ifndef _NEAREST_CENTROID_H__
#define _NEAREST_CENTROID_H__
#include <stdio.h>
#include <shogun/lib/common.h>
#include <shogun/io/SGIO.h>
#include <shogun/features/Features.h>
#include <shogun/features/DenseFeatures.h>
#include <shogun/distance/Distance.h>
#include <shogun/machine/DistanceMachine.h>
namespace shogun
{
class CDistanceMachine;
/** @brief Class NearestCentroid, an implementation of Nearest Shrunk Centroid classifier
*
* To define how close examples are
* NearestCentroid requires a CDistance object to work with (e.g., CEuclideanDistance ).
*/
class CNearestCentroid : public CDistanceMachine{
public:
/** problem type */
MACHINE_PROBLEM_TYPE(PT_MULTICLASS);
/**
* Default constructor
*/
CNearestCentroid();
/** constructor
*
* @param distance distance
* @param trainlab labels for training
*/
CNearestCentroid(CDistance* distance, CLabels* trainlab);
/** Destructor
*/
virtual ~CNearestCentroid();
/** Set shrinking constant
*
* @param shrinking to be set
*/
void set_shrinking(float64_t shrinking) {
m_shrinking = shrinking ;
}
/** Get shrinking constant
*
* @return value of the shrinking constant
*/
float64_t get_shrinking() const{
return m_shrinking;
}
/** Get the centroids
*
* @return Matrix containing the centroids
*/
CDenseFeatures<float64_t>* get_centroids() const{
return m_centroids;
}
/** Returns the name of the SGSerializable instance.
*
* @return name of the SGSerializable
*/
virtual const char* get_name() const { return "NearestCentroid"; }
protected:
/** train Nearest Centroid classifier
*
* @param data training data (parameter can be avoided if distance or
* kernel-based classifiers are used and distance/kernels are
* initialized with train data)
*
* @return whether training was successful
*/
virtual bool train_machine(CFeatures* data=NULL);
/** Stores feature data of underlying model.
*
* Sets centroids as lhs
*/
private:
void init();
protected:
/// number of classes (i.e. number of values labels can take)
int32_t m_num_classes;
/// Shrinking parameter
float64_t m_shrinking;
/// The centroids of the trained features
CDenseFeatures<float64_t>* m_centroids;
/// Tells if the classifier has been trained or not
bool m_is_trained;
};
}
#endif
|