LatentSVM.cpp

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/*
 * This program is free software; you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation; either version 3 of the License, or
 * (at your option) any later version.
 *
 * Written (W) 2012 Viktor Gal
 * Copyright (C) 2012 Viktor Gal
 */

#include <typeinfo>

#include <shogun/classifier/svm/SVMOcas.h>
#include <shogun/latent/LatentSVM.h>

using namespace shogun;

CLatentSVM::CLatentSVM()
    : CLinearLatentMachine()
{
}

CLatentSVM::CLatentSVM(CLatentModel* model, float64_t C)
    : CLinearLatentMachine(model, C)
{
}

CLatentSVM::~CLatentSVM()
{
}

CLatentLabels* CLatentSVM::apply_latent()
{
    if (!m_model)
        SG_ERROR("LatentModel is not set!\n");

    if (!features)
        return NULL;

    index_t num_examples = m_model->get_num_vectors();
    CLatentLabels* hs = new CLatentLabels(num_examples);
    CBinaryLabels* ys = new CBinaryLabels(num_examples);
    hs->set_labels(ys);
    m_model->set_labels(hs);

    for (index_t i = 0; i < num_examples; ++i)
    {
        /* find h for the example */
        CData* h = m_model->infer_latent_variable(w, i);
        hs->add_latent_label(h);
    }

    /* compute the y labels */
    CDotFeatures* x = m_model->get_psi_feature_vectors();
    x->dense_dot_range(ys->get_labels().vector, 0, num_examples, NULL, w.vector, w.vlen, 0.0);

    return hs;
}

float64_t CLatentSVM::do_inner_loop(float64_t cooling_eps)
{
    CLabels* ys = m_model->get_labels()->get_labels();
    CSVMOcas svm(m_C, features, ys);
    svm.set_epsilon(cooling_eps);
    svm.train();
    SG_UNREF(ys);

    /* copy the resulting w */
    SGVector<float64_t> cur_w = svm.get_w();
    memcpy(w.vector, cur_w.vector, cur_w.vlen*sizeof(float64_t));

    return svm.compute_primal_objective();
}