53 arma::mat
eval(
const arma::mat &X,
const arma::mat &Y,
54 bool diag =
false)
const;
67 arma::mat
derivate(
size_t param_id,
const arma::mat &X,
68 const arma::mat &Y,
bool diag =
false)
const;
78 void set_params(
const std::vector<double> ¶ms);
size_t n_params() const
Returns the number of params needed by the kernel.
Definition: kernels.cc:226
std::vector< double > get_params() const
Returns a vector with the current values of the parameters of the kernel.
Definition: kernels.cc:234
void set_lower_bounds(const std::vector< double > &lower_bounds)
Sets the lower bounds to be used by the kernel during training process.
Definition: kernels.cc:238
arma::mat eval(const arma::mat &X, const arma::mat &Y, bool diag=false) const
Evaluates the kernel function over the provided matrices.
Definition: kernels.cc:215
arma::mat derivate(size_t param_id, const arma::mat &X, const arma::mat &Y, bool diag=false) const
Returns the value of the derivative wrt a certain parameter with a a particular pair of input matrice...
Definition: kernels.cc:220
void set_upper_bounds(const std::vector< double > &upper_bounds)
Sets the upper bounds to be used by the kernel during training process.
Definition: kernels.cc:242
implementation * pimpl
Definition: kernels.hpp:26
std::vector< double > get_lower_bounds() const
Returns a vector with the current values of the lower_bounds for each of the parameters of the kernel...
Definition: kernels.cc:245
std::vector< double > get_upper_bounds() const
Returns a vector with the current values of the upper_bounds for each of the parameters of the kernel...
Definition: kernels.cc:249
squared_exponential()
Constructor.
Definition: kernels.cc:202
void set_params(const std::vector< double > ¶ms)
Sets the parameters of the kernel using the proided vector.
Definition: kernels.cc:230
~squared_exponential()
Destructor.
Definition: kernels.cc:211
Squared exponential kernel with noise inference.
Definition: kernels.hpp:21