/usr/include/shogun/distance/MinkowskiMetric.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 | /*
* 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
* Copyright (C) 2006-2009 Fraunhofer Institute FIRST and Max-Planck-Society
*/
#ifndef _MINKOWSKIMETRIC_H___
#define _MINKOWSKIMETRIC_H___
#include <shogun/lib/common.h>
#include <shogun/distance/SimpleDistance.h>
#include <shogun/features/SimpleFeatures.h>
namespace shogun
{
/** @brief class MinkowskiMetric
*
* The Minkowski metric is one general class of metrics for a
* \f$\displaystyle R^{n}\f$ feature space also referred as
* the \f$\displaystyle L_{k} \f$ norm.
*
* \f[ \displaystyle
* d(\bf{x},\bf{x'}) = (\sum_{i=1}^{n} |\bf{x_{i}}-\bf{x'_{i}}|^{k})^{\frac{1}{k}}
* \quad x,x' \in R^{n}
* \f]
*
* special cases:
* -# \f$\displaystyle L_{1} \f$ norm: Manhattan distance @see CManhattanMetric
* -# \f$\displaystyle L_{2} \f$ norm: Euclidean distance @see CEuclidianDistance
*
* Note that the Minkowski distance tends to the Chebyshew distance for
* increasing \f$k\f$.
*
* @see <a href="http://en.wikipedia.org/wiki/Distance">Wikipedia: Distance</a>
*/
class CMinkowskiMetric: public CSimpleDistance<float64_t>
{
public:
/** default constructor */
CMinkowskiMetric();
/** constructor
*
* @param k parameter k
*/
CMinkowskiMetric(float64_t k);
/** constructor
*
* @param l features of left-hand side
* @param r features of right-hand side
* @param k parameter k
*/
CMinkowskiMetric(CSimpleFeatures<float64_t>* l, CSimpleFeatures<float64_t>* r, float64_t k);
virtual ~CMinkowskiMetric();
/** constructor
*
* @param l features of left-hand side
* @param r features of right-hand side
*/
virtual bool init(CFeatures* l, CFeatures* r);
/** cleanup distance */
virtual void cleanup();
/** get distance type we are
*
* @return distance type MINKOWSKI
*/
virtual EDistanceType get_distance_type() { return D_MINKOWSKI;}
/** get name of the distance
*
* @return name Minkowski-Metric
*/
virtual const char* get_name() const { return "MinkowskiMetric"; }
protected:
/// compute distance 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:
/** parameter k */
float64_t k;
};
} // namespace shogun
#endif /* _MINKOWSKIMETRIC_H___ */
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