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/*
* File: linearFunction.cpp
*
* Likelihood, gradient and initialisation of linear function
* Functor, based on mlpack: www.mlpack.org
*/
#include "linkFunction.hpp"
/**
* Evaluate the logistic regression objective function given the estimated
* parameters.
*/
double LinearLikelihood::operator()(const column_vector& parameters_in)
const
{
// Convert from dlib column matrix to armadillo column matrix
arma::vec parameters = dlib_to_arma(parameters_in);
// L(b) = 1/2*||y-Xb||^2
double result = 0.5 * accu(square(responses - predictors * parameters));
return result;
}
// Evaluate the gradient of the logistic regression objective function.
column_vector LinearLikelihoodGradient::operator()(const column_vector& parameters_in)
const
{
// Convert from dlib column matrix to armadillo column matrix
arma::vec parameters = dlib_to_arma(parameters_in);
arma::vec gradient(parameters.n_elem);
// dL(b)/db = X.t()(Xb - y)
gradient = predictors.t() * (predictors * parameters - responses);
return arma_to_dlib(gradient);
}
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