softmax_regression_function.hpp

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#ifndef MLPACK_METHODS_SOFTMAX_REGRESSION_SOFTMAX_REGRESSION_FUNCTION_HPP
#define MLPACK_METHODS_SOFTMAX_REGRESSION_SOFTMAX_REGRESSION_FUNCTION_HPP

#include <mlpack/prereqs.hpp>

namespace mlpack {
namespace regression {

class SoftmaxRegressionFunction
{
 public:
  SoftmaxRegressionFunction(const arma::mat& data,
                            const arma::Row<size_t>& labels,
                            const size_t numClasses,
                            const double lambda = 0.0001,
                            const bool fitIntercept = false);

  const arma::mat InitializeWeights();

  static const arma::mat InitializeWeights(const size_t featureSize,
                                           const size_t numClasses,
                                           const bool fitIntercept = false);

  static void InitializeWeights(arma::mat &weights,
                                const size_t featureSize,
                                const size_t numClasses,
                                const bool fitIntercept = false);

  void GetGroundTruthMatrix(const arma::Row<size_t>& labels,
                            arma::sp_mat& groundTruth);

  void GetProbabilitiesMatrix(const arma::mat& parameters,
                              arma::mat& probabilities) const;

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

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

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

  size_t NumClasses() const { return numClasses; }

  size_t FeatureSize() const
  {
    return fitIntercept ? initialPoint.n_cols - 1 :
                          initialPoint.n_cols;
  }

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

  bool FitIntercept() const { return fitIntercept; }

 private:
  const arma::mat& data;
  arma::sp_mat groundTruth;
  arma::mat initialPoint;
  size_t numClasses;
  double lambda;
  bool fitIntercept;
};

} // namespace regression
} // namespace mlpack

#endif