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