/usr/include/shogun/distance/EuclidianDistance.h is in libshogun-dev 1.1.0-4ubuntu2.
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* 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) 2007-2009 Soeren Sonnenburg
* Copyright (C) 2007-2009 Fraunhofer Institute FIRST and Max-Planck-Society
*/
#ifndef _EUCLIDIANDISTANCE_H__
#define _EUCLIDIANDISTANCE_H__
#include <shogun/lib/common.h>
#include <shogun/distance/RealDistance.h>
#include <shogun/features/SimpleFeatures.h>
namespace shogun
{
/** @brief class EuclidianDistance
*
* The familiar Euclidian distance for real valued features computes
* the square root of the sum of squared disparity between the
* corresponding feature dimensions of two data points.
*
* \f[\displaystyle
* d({\bf x},{\bf x'})= \sqrt{\sum_{i=0}^{n}|{\bf x_i}-{\bf x'_i}|^2}
* \f]
*
* This special case of Minkowski metric is invariant to an arbitrary
* translation or rotation in feature space.
*
* The Euclidian Squared distance does not take the square root:
*
* \f[\displaystyle
* d({\bf x},{\bf x'})= \sum_{i=0}^{n}|{\bf x_i}-{\bf x'_i}|^2
* \f]
*
* @see CMinkowskiMetric
* @see <a href="http://en.wikipedia.org/wiki/Distance#Distance_in_Euclidean_space">
* Wikipedia: Distance in Euclidean space</a>
*/
class CEuclidianDistance: public CRealDistance
{
public:
/** default constructor */
CEuclidianDistance();
/** constructor
*
* @param l features of left-hand side
* @param r features of right-hand side
*/
CEuclidianDistance(CSimpleFeatures<float64_t>* l, CSimpleFeatures<float64_t>* r);
virtual ~CEuclidianDistance();
/** 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_EUCLIDIAN; }
/** 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 "EuclidianDistance"; }
/** 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 /* _EUCLIDIANDISTANCE_H__ */
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