linear_regression.hpp

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#ifndef MLPACK_METHODS_LINEAR_REGRESSION_LINEAR_REGRESSION_HPP
#define MLPACK_METHODS_LINEAR_REGRESSION_LINEAR_REGRESSION_HPP
 
#include <mlpack/prereqs.hpp>
 
namespace mlpack {
namespace regression  {
 
class LinearRegression
{
 public:
  LinearRegression(const arma::mat& predictors,
                   const arma::rowvec& responses,
                   const double lambda = 0,
                   const bool intercept = true);
 
  LinearRegression(const arma::mat& predictors,
                   const arma::rowvec& responses,
                   const arma::rowvec& weights,
                   const double lambda = 0,
                   const bool intercept = true);
 
  LinearRegression() : lambda(0.0), intercept(true) { }
 
  double Train(const arma::mat& predictors,
               const arma::rowvec& responses,
               const bool intercept = true);
 
  double Train(const arma::mat& predictors,
               const arma::rowvec& responses,
               const arma::rowvec& weights,
               const bool intercept = true);
 
  void Predict(const arma::mat& points, arma::rowvec& predictions) const;
 
  double ComputeError(const arma::mat& points,
                      const arma::rowvec& responses) const;
 
  const arma::vec& Parameters() const { return parameters; }
  arma::vec& Parameters() { return parameters; }
 
  double Lambda() const { return lambda; }
  double& Lambda() { return lambda; }
 
  bool Intercept() const { return intercept; }
 
  template<typename Archive>
  void serialize(Archive& ar, const unsigned int /* version */)
  {
    ar & BOOST_SERIALIZATION_NVP(parameters);
    ar & BOOST_SERIALIZATION_NVP(lambda);
    ar & BOOST_SERIALIZATION_NVP(intercept);
  }
 
 private:
  arma::vec parameters;
 
  double lambda;
 
  bool intercept;
};
 
} // namespace regression
} // namespace mlpack
 
#endif // MLPACK_METHODS_LINEAR_REGRESSION_HPP