mlpack
kernel_traits.hpp
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1 
13 #ifndef MLPACK_CORE_KERNELS_KERNEL_TRAITS_HPP
14 #define MLPACK_CORE_KERNELS_KERNEL_TRAITS_HPP
15 
16 namespace mlpack {
17 namespace kernel {
18 
26 template<typename KernelType>
27 class KernelTraits
28 {
29  public:
33  static const bool IsNormalized = false;
34 
38  static const bool UsesSquaredDistance = false;
39 };
40 
41 } // namespace kernel
42 } // namespace mlpack
43 
44 #endif
mlpack::kernel::KernelTraits
This is a template class that can provide information about various kernels.
Definition: kernel_traits.hpp:27
mlpack
Linear algebra utility functions, generally performed on matrices or vectors.
Definition: add_to_cli11.hpp:21
mlpack::kernel::KernelTraits::IsNormalized
static const bool IsNormalized
If true, then the kernel is normalized: K(x, x) = K(y, y) = 1 for all x.
Definition: kernel_traits.hpp:33
mlpack::kernel::KernelTraits::UsesSquaredDistance
static const bool UsesSquaredDistance
If true, then the kernel include a squared distance, ||x - y||^2 .
Definition: kernel_traits.hpp:38