14 #ifndef MLPACK_METHODS_LOGISTIC_REGRESSION_LOGISTIC_REGRESSION_FUNCTION_HPP    15 #define MLPACK_METHODS_LOGISTIC_REGRESSION_LOGISTIC_REGRESSION_FUNCTION_HPP    22 namespace regression {
    29 template<
typename MatType = arma::mat>
    41                              const arma::Row<size_t>& responses,
    42                              const double lambda = 0);
    45   const double& 
Lambda()
 const { 
return lambda; }
    52   const arma::Row<size_t>& 
Responses()
 const { 
return responses; }
    70   double Evaluate(
const arma::mat& parameters) 
const;
    89   double Evaluate(
const arma::mat& parameters,
    91                   const size_t batchSize = 1) 
const;
   100   void Gradient(
const arma::mat& parameters, arma::mat& gradient) 
const;
   115   template<
typename GradType>
   116   void Gradient(
const arma::mat& parameters,
   119                 const size_t batchSize = 1) 
const;
   134                        arma::sp_mat& gradient) 
const;
   140   template<
typename GradType>
   142                               GradType& gradient) 
const;
   149   template<
typename GradType>
   153                               const size_t batchSize = 1) 
const;
   167   arma::Row<size_t> responses;
   176 #include "logistic_regression_function_impl.hpp"   178 #endif // MLPACK_METHODS_LOGISTIC_REGRESSION_LOGISTIC_REGRESSION_FUNCTION_HPP LogisticRegressionFunction(const MatType &predictors, const arma::Row< size_t > &responses, const double lambda=0)
Creates the LogisticRegressionFunction. 
 
The log-likelihood function for the logistic regression objective function. 
 
Linear algebra utility functions, generally performed on matrices or vectors. 
 
double Evaluate(const arma::mat ¶meters) const
Evaluate the logistic regression log-likelihood function with the given parameters. 
 
The core includes that mlpack expects; standard C++ includes and Armadillo. 
 
const double & Lambda() const
Return the regularization parameter (lambda). 
 
double EvaluateWithGradient(const arma::mat ¶meters, GradType &gradient) const
Evaluate the objective function and gradient of the logistic regression log-likelihood function simul...
 
size_t NumFunctions() const
Return the number of separable functions (the number of predictor points). 
 
void Shuffle()
Shuffle the order of function visitation. 
 
const MatType & Predictors() const
Return the matrix of predictors. 
 
const arma::Row< size_t > & Responses() const
Return the vector of responses. 
 
double & Lambda()
Modify the regularization parameter (lambda). 
 
void PartialGradient(const arma::mat ¶meters, const size_t j, arma::sp_mat &gradient) const
Evaluate the gradient of the logistic regression log-likelihood function with the given parameters...
 
size_t NumFeatures() const
Return the number of features(add 1 for the intercept term). 
 
void Gradient(const arma::mat ¶meters, arma::mat &gradient) const
Evaluate the gradient of the logistic regression log-likelihood function with the given parameters...