12 #ifndef MLPACK_METHODS_ANN_DISTRIBUTIONS_BERNOULLI_DISTRIBUTION_HPP    13 #define MLPACK_METHODS_ANN_DISTRIBUTIONS_BERNOULLI_DISTRIBUTION_HPP    16 #include "../activation_functions/logistic_function.hpp"    33 template <
typename DataType = arma::mat>
    64                         const bool applyLogistic = 
true,
    65                         const double eps = 1e-10);
    91   void LogProbBackward(
const DataType& observation, DataType& output) 
const;
   108   const DataType& 
Logits()
 const { 
return logits; }
   116   template<
typename Archive>
   120     ar(CEREAL_NVP(probability));
   121     ar(CEREAL_NVP(logits));
   122     ar(CEREAL_NVP(applyLogistic));
   128   DataType probability;
   145 #include "bernoulli_distribution_impl.hpp" const DataType & Probability() const
Return the probability matrix. 
 
void LogProbBackward(const DataType &observation, DataType &output) const
Stores the gradient of the log probabilities of the observations in the output matrix. 
 
Linear algebra utility functions, generally performed on matrices or vectors. 
 
void serialize(Archive &ar, const uint32_t)
Serialize the distribution. 
 
The core includes that mlpack expects; standard C++ includes and Armadillo. 
 
double LogProbability(const DataType &observation) const
Return the log probabilities of the given matrix of observations. 
 
const DataType & Logits() const
Return the logits matrix. 
 
Multiple independent Bernoulli distributions. 
 
double Probability(const DataType &observation) const
Return the probabilities of the given matrix of observations. 
 
DataType & Logits()
Return a modifiable copy of the pre probability matrix. 
 
DataType & Probability()
Return a modifiable copy of the probability matrix. 
 
BernoulliDistribution()
Default constructor, which creates a Bernoulli distribution with zero dimension. 
 
DataType Sample() const
Return a matrix of randomly generated samples according to the probability distributions defined by t...