cauchy_kernel.hpp

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#ifndef MLPACK_CORE_KERNELS_CAUCHY_KERNEL_HPP
#define MLPACK_CORE_KERNELS_CAUCHY_KERNEL_HPP

#include <mlpack/prereqs.hpp>
#include <mlpack/core/metrics/lmetric.hpp>
#include <mlpack/core/kernels/kernel_traits.hpp>

namespace mlpack {
namespace kernel {

class CauchyKernel
{
 public:
  CauchyKernel(double bandwidth = 1.0) : bandwidth(bandwidth)
  { }

  template<typename VecTypeA, typename VecTypeB>
  double Evaluate(const VecTypeA& a, const VecTypeB& b)
  {
    return 1 / (1 + (
        std::pow(metric::EuclideanDistance::Evaluate(a, b) / bandwidth, 2)));
  }

  template<typename Archive>
  void serialize(Archive& ar, const uint32_t /* version */)
  {
    ar(CEREAL_NVP(bandwidth));
  }

 private:
  double bandwidth;
};

template<>
class KernelTraits<CauchyKernel>
{
 public:
  static const bool IsNormalized = true;
};

} // namespace kernel
} // namespace mlpack

#endif