mlpack 3.4.2
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
16namespace mlpack {
17namespace kernel {
18
26template<typename KernelType>
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
This is a template class that can provide information about various kernels.
static const bool UsesSquaredDistance
If true, then the kernel include a squared distance, ||x - y||^2 .
static const bool IsNormalized
If true, then the kernel is normalized: K(x, x) = K(y, y) = 1 for all x.
Linear algebra utility functions, generally performed on matrices or vectors.
Definition: cv.hpp:1