SVMLightOneClass.cpp

Go to the documentation of this file.

/*
 * 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/lib/config.h>

#ifdef USE_SVMLIGHT

#include <shogun/io/SGIO.h>
#include <shogun/mathematics/lapack.h>
#include <shogun/lib/Signal.h>
#include <shogun/labels/BinaryLabels.h>
#include <shogun/mathematics/Math.h>
#include <shogun/classifier/svm/SVMLightOneClass.h>
#include <shogun/machine/KernelMachine.h>
#include <shogun/kernel/CombinedKernel.h>

#include <unistd.h>

#ifdef USE_CPLEX
extern "C" {
#include <ilcplex/cplex.h>
}
#endif

#include <shogun/base/Parallel.h>

#ifdef HAVE_PTHREAD
#include <pthread.h>
#endif

using namespace shogun;

CSVMLightOneClass::CSVMLightOneClass(float64_t C, CKernel* k)
: CSVMLight()
{
    set_C(C,C);
    set_kernel(k);
}

CSVMLightOneClass::CSVMLightOneClass()
: CSVMLight()
{
}

bool CSVMLightOneClass::train_machine(CFeatures* data)
{
    //certain setup params
    mkl_converged=false;
    verbosity=1 ;
    init_margin=0.15;
    init_iter=500;
    precision_violations=0;
    opt_precision=DEF_PRECISION;

    strcpy (learn_parm->predfile, "");
    learn_parm->biased_hyperplane=0;
    learn_parm->sharedslack=0;
    learn_parm->remove_inconsistent=0;
    learn_parm->skip_final_opt_check=0;
    learn_parm->svm_maxqpsize=get_qpsize();
    learn_parm->svm_newvarsinqp=learn_parm->svm_maxqpsize-1;
    learn_parm->maxiter=100000;
    learn_parm->svm_iter_to_shrink=100;
    learn_parm->svm_c=C1;
    learn_parm->transduction_posratio=0.33;
    learn_parm->svm_costratio=C2/C1;
    learn_parm->svm_costratio_unlab=1.0;
    learn_parm->svm_unlabbound=1E-5;
    learn_parm->epsilon_crit=epsilon; // GU: better decrease it ... ??
    learn_parm->epsilon_a=1E-15;
    learn_parm->compute_loo=0;
    learn_parm->rho=1.0;
    learn_parm->xa_depth=0;

    if (!kernel)
        SG_ERROR( "SVM_light can not proceed without kernel!\n");

    if (data)
        kernel->init(data, data);

    if (!kernel->has_features())
        SG_ERROR( "SVM_light can not proceed without initialized kernel!\n");

    int32_t num_vec=kernel->get_num_vec_lhs();
    SG_INFO("num_vec=%d\n", num_vec);

    SG_UNREF(m_labels);
    m_labels=new CBinaryLabels(num_vec);
    ((CBinaryLabels*) m_labels)->set_to_one();

    // in case of LINADD enabled kernels cleanup!
    if (kernel->has_property(KP_LINADD) && get_linadd_enabled())
        kernel->clear_normal() ;

    // output some info
    SG_DEBUG( "threads = %i\n", parallel->get_num_threads()) ;
    SG_DEBUG( "qpsize = %i\n", learn_parm->svm_maxqpsize) ;
    SG_DEBUG( "epsilon = %1.1e\n", learn_parm->epsilon_crit) ;
    SG_DEBUG( "kernel->has_property(KP_LINADD) = %i\n", kernel->has_property(KP_LINADD)) ;
    SG_DEBUG( "kernel->has_property(KP_KERNCOMBINATION) = %i\n", kernel->has_property(KP_KERNCOMBINATION)) ;
    SG_DEBUG( "kernel->has_property(KP_BATCHEVALUATION) = %i\n", kernel->has_property(KP_BATCHEVALUATION)) ;
    SG_DEBUG( "kernel->get_optimization_type() = %s\n", kernel->get_optimization_type()==FASTBUTMEMHUNGRY ? "FASTBUTMEMHUNGRY" : "SLOWBUTMEMEFFICIENT" ) ;
    SG_DEBUG( "get_solver_type() = %i\n", get_solver_type());
    SG_DEBUG( "get_linadd_enabled() = %i\n", get_linadd_enabled()) ;
    SG_DEBUG( "get_batch_computation_enabled() = %i\n", get_batch_computation_enabled()) ;
    SG_DEBUG( "kernel->get_num_subkernels() = %i\n", kernel->get_num_subkernels()) ;

    use_kernel_cache = !((kernel->get_kernel_type() == K_CUSTOM) ||
                         (get_linadd_enabled() && kernel->has_property(KP_LINADD)));

    SG_DEBUG( "use_kernel_cache = %i\n", use_kernel_cache) ;

    if (kernel->get_kernel_type() == K_COMBINED)
    {
        CKernel* kn = ((CCombinedKernel*)kernel)->get_first_kernel();

        while (kn)
        {
            // allocate kernel cache but clean up beforehand
            kn->resize_kernel_cache(kn->get_cache_size());
            SG_UNREF(kn);
            kn = ((CCombinedKernel*) kernel)->get_next_kernel();
        }
    }

    kernel->resize_kernel_cache(kernel->get_cache_size());

    // train the svm
    svm_learn();

    // brain damaged svm light work around
    create_new_model(model->sv_num-1);
    set_bias(-model->b);
    for (int32_t i=0; i<model->sv_num-1; i++)
    {
        set_alpha(i, model->alpha[i+1]);
        set_support_vector(i, model->supvec[i+1]);
    }

    // in case of LINADD enabled kernels cleanup!
    if (kernel->has_property(KP_LINADD) && get_linadd_enabled())
    {
        kernel->clear_normal() ;
        kernel->delete_optimization() ;
    }

    if (use_kernel_cache)
        kernel->kernel_cache_cleanup();

    return true ;
}
#endif //USE_SVMLIGHT