MultinomialSupervisedEStep.hpp

#ifndef _LDAPLUSPLUS_EM_MULTINOMIALSUPERVISEDESTEP_HPP_
#define _LDAPLUSPLUS_EM_MULTINOMIALSUPERVISEDESTEP_HPP__

#include "ldaplusplus/em/AbstractEStep.hpp"

namespace ldaplusplus {
namespace em {


template<typename Scalar>
class MultinomialSupervisedEStep: public AbstractEStep<Scalar>
{
    typedef Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> MatrixX;
    typedef Eigen::Matrix<Scalar, Eigen::Dynamic, 1> VectorX;

    public:
        MultinomialSupervisedEStep(
            size_t e_step_iterations = 10,
            Scalar e_step_tolerance = 1e-2,
            Scalar mu = 2,
            Scalar eta_weight = 1,
            Scalar compute_likelihood = 1.0,
            int random_state = 0
        );

        std::shared_ptr<parameters::Parameters> doc_e_step(
            const std::shared_ptr<corpus::Document> doc,
            const std::shared_ptr<parameters::Parameters> parameters
        ) override;

    private:
        // The maximum number of iterations in E-step.
        size_t e_step_iterations_;
        // The convergence tolerance for the maximazation of the ELBO w.r.t.
        // phi and gamma in E-step.
        Scalar e_step_tolerance_;
        // The Dirichlet prior for the class predicting parameters.
        Scalar mu_;
        // A weighting parameter that either increases or decreases the
        // influence of the supervised part.
        Scalar eta_weight_;
        // Compute the likelihood of that many documents (pecentile)
        Scalar compute_likelihood_;
};

}  // namespace em
}  // namespace ldaplusplus

#endif   // _LDAPLUSPLUS_EM_MULTINOMIALSUPERVISEDESTEP_HPP_