logistic_regression_function.hpp

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#ifndef MLPACK_METHODS_LOGISTIC_REGRESSION_LOGISTIC_REGRESSION_FUNCTION_HPP
#define MLPACK_METHODS_LOGISTIC_REGRESSION_LOGISTIC_REGRESSION_FUNCTION_HPP

#include <mlpack/prereqs.hpp>

namespace mlpack {
namespace regression {

template<typename MatType = arma::mat>
class LogisticRegressionFunction
{
 public:
  LogisticRegressionFunction(const MatType& predictors,
                             const arma::Row<size_t>& responses,
                             const double lambda = 0);

  LogisticRegressionFunction(const MatType& predictors,
                             const arma::Row<size_t>& responses,
                             const arma::vec& initialPoint,
                             const double lambda = 0);

  const arma::mat& InitialPoint() const { return initialPoint; }
  arma::mat& InitialPoint() { return initialPoint; }

  const double& Lambda() const { return lambda; }
  double& Lambda() { return lambda; }

  const MatType& Predictors() const { return predictors; }
  const arma::Row<size_t>& Responses() const { return responses; }

  void Shuffle();

  double Evaluate(const arma::mat& parameters) const;

  double Evaluate(const arma::mat& parameters,
                  const size_t begin,
                  const size_t batchSize = 1) const;

  void Gradient(const arma::mat& parameters, arma::mat& gradient) const;

  template<typename GradType>
  void Gradient(const arma::mat& parameters,
                const size_t begin,
                GradType& gradient,
                const size_t batchSize = 1) const;

  void PartialGradient(const arma::mat& parameters,
                       const size_t j,
                       arma::sp_mat& gradient) const;

  template<typename GradType>
  double EvaluateWithGradient(const arma::mat& parameters,
                              GradType& gradient) const;

  template<typename GradType>
  double EvaluateWithGradient(const arma::mat& parameters,
                              const size_t begin,
                              GradType& gradient,
                              const size_t batchSize = 1) const;

  const arma::mat& GetInitialPoint() const { return initialPoint; }

  size_t NumFunctions() const { return predictors.n_cols; }

  size_t NumFeatures() const { return predictors.n_rows + 1; }

 private:
  arma::mat initialPoint;
  MatType predictors;
  arma::Row<size_t> responses;
  double lambda;
};

} // namespace regression
} // namespace mlpack

// Include implementation.
#include "logistic_regression_function_impl.hpp"

#endif // MLPACK_METHODS_LOGISTIC_REGRESSION_LOGISTIC_REGRESSION_FUNCTION_HPP