/usr/include/shogun/distance/AttenuatedEuclidianDistance.h is in libshogun-dev 1.1.0-4ubuntu2.
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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 | /*
* 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) 2011 Miguel Angel Bautista
* Copyright (C) 2011 Berlin Institute of Technology and Max Planck Society
*/
#ifndef _ATTENUATEDEUCLIDIANDISTANCE_H__
#define _ATTENUATEDEUCLIDIANDISTANCE_H__
#include <shogun/lib/common.h>
#include <shogun/distance/RealDistance.h>
#include <shogun/features/SimpleFeatures.h>
namespace shogun
{
/** @brief class AttenuatedEuclidianDistance
*
* The adaptation of the familiar Euclidean Distance, to be used in
* ternary ECOC designs. This adaptation computes the Euclidean distance
* between two vectors ignoring those positions of either of the vectors
* valued as 0. Note that this might make sense only in the Decoding
* step of the ECOC framework, since the 0 value denotes that a certain category is
* ignored.
*
* This distance was proposed by
* S. Escalera, O. Pujol, P.Radeva in On the decoding process in ternary error-correcting output codes,
* Transactions in Pattern Analysis and Machine Intelligence 99 (1).
*
* \f[\displaystyle
* d({\bf x},{\bf x'})= \sqrt{\sum_{i=0}^{n}|x_i||x'_i|{\bf x_i}-{\bf x'_i}|^2}
* \f]
*
*/
class CAttenuatedEuclidianDistance: public CRealDistance
{
public:
/** default constructor */
CAttenuatedEuclidianDistance();
/** constructor
*
* @param l features of left-hand side
* @param r features of right-hand side
*/
CAttenuatedEuclidianDistance(CSimpleFeatures<float64_t>* l, CSimpleFeatures<float64_t>* r);
virtual ~CAttenuatedEuclidianDistance();
/** init distance
*
* @param l features of left-hand side
* @param r features of right-hand side
* @return if init was successful
*/
virtual bool init(CFeatures* l, CFeatures* r);
/** cleanup distance */
virtual void cleanup();
/** get distance type we are
*
* @return distance type EUCLIDIAN
*/
virtual EDistanceType get_distance_type() { return D_ATTENUATEDEUCLIDIAN; }
/** get feature type the distance can deal with
*
* @return feature type DREAL
*/
inline virtual EFeatureType get_feature_type() { return F_DREAL; }
/** get name of the distance
*
* @return name Euclidian
*/
virtual const char* get_name() const { return "AttenuatedEuclidianDistance"; }
/** disable application of sqrt on matrix computation
* the matrix can then also be named norm squared
*
* @return if application of sqrt is disabled
*/
virtual bool get_disable_sqrt() { return disable_sqrt; };
/** disable application of sqrt on matrix computation
* the matrix can then also be named norm squared
*
* @param state new disable_sqrt
*/
virtual void set_disable_sqrt(bool state) { disable_sqrt=state; };
protected:
/// compute kernel function for features a and b
/// idx_{a,b} denote the index of the feature vectors
/// in the corresponding feature object
virtual float64_t compute(int32_t idx_a, int32_t idx_b);
private:
void init();
protected:
/** if application of sqrt on matrix computation is disabled */
bool disable_sqrt;
};
} // namespace shogun
#endif /* _ATTENUATEDEUCLIDIANDISTANCE_H__ */
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