LogitDVGLikelihood.cpp

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/*
 * Copyright (c) The Shogun Machine Learning Toolbox
 * Written (w) 2014 Wu Lin
 * All rights reserved.
 *
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 * modification, are permitted provided that the following conditions are met:
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 *    list of conditions and the following disclaimer.
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#include <shogun/machine/gp/LogitDVGLikelihood.h>

#ifdef HAVE_EIGEN3
#include <shogun/mathematics/eigen3.h>
#include <shogun/machine/gp/LogitVGLikelihood.h>
#include <shogun/mathematics/Statistics.h>
#include <shogun/distributions/classical/GaussianDistribution.h>
#include <shogun/mathematics/Math.h>
#include <shogun/labels/BinaryLabels.h>

using namespace Eigen;

namespace shogun
{

CLogitDVGLikelihood::CLogitDVGLikelihood()
    : CDualVariationalGaussianLikelihood()
{
    init();
}

CLogitDVGLikelihood::~CLogitDVGLikelihood()
{
}

SGVector<float64_t> CLogitDVGLikelihood::get_variance_dual_parameter() const
{
    SGVector<float64_t> lambda=m_lambda.clone();

    return lambda;
}

SGVector<float64_t> CLogitDVGLikelihood::get_mu_dual_parameter() const
{
    SGVector<float64_t> alpha=m_lambda.clone();

    for (index_t i=0; i<alpha.vlen; i++)
        alpha[i]-=m_lab[i];

    return alpha;
}

SGVector<float64_t> CLogitDVGLikelihood::get_dual_objective_value()
{
    SGVector<float64_t> result(m_lambda.vlen);

    if (!m_is_valid)
    {
        Map<VectorXd> eigen_reslut(result.vector, result.vlen);
        eigen_reslut.fill(CMath::INFTY);
        return result;
    }

    for (index_t i=0; i<result.vlen; ++i)
    {
        float64_t lambda=m_lambda[i];
        result[i]=lambda*CMath::log(lambda)+(1.0-lambda)*CMath::log(1.0-lambda);
    }
    return result;
}

SGVector<float64_t> CLogitDVGLikelihood::get_dual_first_derivative(
        const TParameter* param) const
{
    REQUIRE(param, "Param is required (param should not be NULL)\n");
    REQUIRE(param->m_name, "Param name is required (param->m_name should not be NULL)\n");
    REQUIRE(!strcmp(param->m_name, "lambda"),
        "Can't compute derivative of the variational expection ",
        "of log LogitLikelihood in dual setting",
        "wrt %s.%s parameter. The function only accepts lambda as parameter\n",
        get_name(), param->m_name);

    SGVector<float64_t> result(m_lambda.vlen);

    if (!m_is_valid)
    {
        Map<VectorXd> eigen_reslut(result.vector, result.vlen);
        eigen_reslut.fill(CMath::INFTY);
        return result;
    }

    for (index_t i=0; i<result.vlen; ++i)
    {
        float64_t lambda=m_lambda[i];
        result[i]=CMath::log(lambda)-CMath::log(1.0-lambda);
    }
    return result;
}

void CLogitDVGLikelihood::init_likelihood()
{
    set_likelihood(new CLogitVGLikelihood());
}

void CLogitDVGLikelihood::init()
{
    init_likelihood();
}

} /* namespace shogun */
#endif /* HAVE_EIGEN3 */