CPLEXSVM.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) 1999-2009 Soeren Sonnenburg
 * Copyright (C) 1999-2009 Fraunhofer Institute FIRST and Max-Planck-Society
 */

#include <shogun/classifier/svm/CPLEXSVM.h>
#include <shogun/lib/common.h>

#ifdef USE_CPLEX
#include <shogun/io/SGIO.h>
#include <shogun/mathematics/Math.h>
#include <shogun/mathematics/Cplex.h>
#include <shogun/labels/Labels.h>

using namespace shogun;

CCPLEXSVM::CCPLEXSVM()
: CSVM()
{
}

CCPLEXSVM::~CCPLEXSVM()
{
}

bool CCPLEXSVM::train_machine(CFeatures* data)
{
    ASSERT(m_labels)
    ASSERT(m_labels->get_label_type() == LT_BINARY)

    bool result = false;
    CCplex cplex;

    if (data)
    {
        if (m_labels->get_num_labels() != data->get_num_vectors())
        {
            SG_ERROR("%s::train_machine(): Number of training vectors (%d) does"
                    " not match number of labels (%d)\n", get_name(),
                    data->get_num_vectors(), m_labels->get_num_labels());
        }
        kernel->init(data, data);
    }

    if (cplex.init(E_QP))
    {
        int32_t n,m;
        int32_t num_label=0;
        SGVector<float64_t> y=((CBinaryLabels*)m_labels)->get_labels();
        SGMatrix<float64_t> H=kernel->get_kernel_matrix();
        m=H.num_rows;
        n=H.num_cols;
        ASSERT(n>0 && n==m && n==num_label)
        float64_t* alphas=SG_MALLOC(float64_t, n);
        float64_t* lb=SG_MALLOC(float64_t, n);
        float64_t* ub=SG_MALLOC(float64_t, n);

        //hessian y'y.*K
        for (int32_t i=0; i<n; i++)
        {
            lb[i]=0;
            ub[i]=get_C1();

            for (int32_t j=0; j<n; j++)
                H[i*n+j]*=y[j]*y[i];
        }

        //feed qp to cplex


        int32_t j=0;
        for (int32_t i=0; i<n; i++)
        {
            if (alphas[i]>0)
            {
                //set_alpha(j, alphas[i]*labels->get_label(i)/etas[1]);
                set_alpha(j, alphas[i]*((CBinaryLabels*) m_labels)->get_int_label(i));
                set_support_vector(j, i);
                j++;
            }
        }
        //compute_objective();
        SG_INFO("obj = %.16f, rho = %.16f\n",get_objective(),get_bias())
        SG_INFO("Number of SV: %ld\n", get_num_support_vectors())

        SG_FREE(alphas);
        SG_FREE(lb);
        SG_FREE(ub);

        result = true;
    }

    if (!result)
        SG_ERROR("cplex svm failed")

    return result;
}
#endif