BayesOpt
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Kernel for categorical data. More...
#include <kernel_hamming.hpp>
Public Member Functions | |
void | init (size_t input_dim) |
size_t | hammingDistance (const vectori &s1, const vectori &s2) |
double | operator() (const vectord &x1, const vectord &x2) |
double | gradient (const vectord &x1, const vectord &x2, size_t component) |
Public Member Functions inherited from bayesopt::AtomicKernel | |
void | setHyperParameters (const vectord &theta) |
vectord | getHyperParameters () |
size_t | nHyperParameters () |
Public Member Functions inherited from bayesopt::Kernel | |
virtual void | init (size_t input_dim, Kernel *left, Kernel *right) |
Additional Inherited Members | |
Protected Attributes inherited from bayesopt::AtomicKernel | |
size_t | n_params |
vectord | params |
Protected Attributes inherited from bayesopt::Kernel | |
size_t | n_inputs |
Kernel for categorical data.
It measures the hamming distance between vectors.
Definition at line 37 of file kernel_hamming.hpp.