27 #ifndef MLPACK_METHODS_ANN_INIT_RULES_OIVS_INIT_HPP    28 #define MLPACK_METHODS_ANN_INIT_RULES_OIVS_INIT_HPP    57     class ActivationFunction = LogisticFunction
    71                      const double gamma = 0.9) :
    73       b(
std::abs(ActivationFunction::Inv(1 - epsilon) -
    74                  ActivationFunction::Inv(epsilon)))
    86   void Initialize(arma::Mat<eT>& W, 
const size_t rows, 
const size_t cols)
    91     W = (b / (k  * rows)) * arma::sqrt(W + 1);
   105     W = (b / (k  * W.n_rows)) * arma::sqrt(W + 1);
   117   template<
typename eT>
   124       W.set_size(rows, cols, slices);
   126     for (
size_t i = 0; i < slices; ++i)
   136   template<
typename eT>
   140       Log::Fatal << 
"Cannot initialize an empty cube." << std::endl;
   142     for (
size_t i = 0; i < W.n_slices; ++i)
 
Linear algebra utility functions, generally performed on matrices or vectors. 
 
This class is used to initialize randomly the weight matrix. 
 
The core includes that mlpack expects; standard C++ includes and Armadillo. 
 
This class is used to initialize the weight matrix with the oivs method. 
 
void Initialize(arma::Mat< eT > &W, const size_t rows, const size_t cols)
Initialize the elements of the specified weight matrix with the oivs method. 
 
void Initialize(arma::Cube< eT > &W)
Initialize the elements of the specified weight 3rd order tensor with the oivs method. 
 
void Initialize(arma::Mat< eT > &W, const size_t rows, const size_t cols)
Initialize randomly the elements of the specified weight matrix. 
 
static MLPACK_EXPORT util::PrefixedOutStream Fatal
Prints fatal messages prefixed with [FATAL], then terminates the program. 
 
void Initialize(arma::Mat< eT > &W)
Initialize the elements of the specified weight matrix with the oivs method. 
 
void Initialize(arma::Cube< eT > &W, const size_t rows, const size_t cols, const size_t slices)
Initialize the elements of the specified weight 3rd order tensor with the oivs method. 
 
OivsInitialization(const double epsilon=0.1, const int k=5, const double gamma=0.9)
Initialize the random initialization rule with the given values.