BinaryLabels.cpp

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#include <shogun/labels/DenseLabels.h>
#include <shogun/labels/BinaryLabels.h>
#include <shogun/mathematics/Statistics.h>

using namespace shogun;

CBinaryLabels::CBinaryLabels() : CDenseLabels()
{
}

CBinaryLabels::CBinaryLabels(int32_t num_labels) : CDenseLabels(num_labels)
{
}

#if !defined(SWIGJAVA) && !defined(SWIGCSHARP)
CBinaryLabels::CBinaryLabels(SGVector<int32_t> src) : CDenseLabels()
{
    SGVector<float64_t> values(src.vlen);
    for (int32_t i=0; i<values.vlen; i++)
        values[i] = src[i];
    set_int_labels(src);
    set_values(values);
}

CBinaryLabels::CBinaryLabels(SGVector<int64_t> src) : CDenseLabels()
{
    SGVector<float64_t> values(src.vlen);
    for (int32_t i=0; i<values.vlen; i++)
        values[i] = src[i];
    set_int_labels(src);
    set_values(values);
}
#endif

CBinaryLabels::CBinaryLabels(SGVector<float64_t> src, float64_t threshold) : CDenseLabels()
{
    SGVector<float64_t> labels(src.vlen);
    for (int32_t i=0; i<labels.vlen; i++)
        labels[i] = src[i]+threshold>=0 ? +1.0 : -1.0;
    set_labels(labels);
    set_values(src);
}

CBinaryLabels::CBinaryLabels(CFile* loader) : CDenseLabels(loader)
{
}

void CBinaryLabels::ensure_valid(const char* context)
{
    CDenseLabels::ensure_valid(context);
    bool found_plus_one=false;
    bool found_minus_one=false;

    int32_t subset_size=get_num_labels();
    for (int32_t i=0; i<subset_size; i++)
    {
        int32_t real_i=m_subset_stack->subset_idx_conversion(i);
        if (m_labels[real_i]==+1.0)
            found_plus_one=true;
        else if (m_labels[real_i]==-1.0)
            found_minus_one=true;
        else
        {
            SG_ERROR(
                    "%s%s%s::ensure_valid(): Not a two class labeling label[%d]=%f (only +1/-1 "
                            "allowed)\n", context ? context : "",
                    context ? ": " : "", get_name(), i, m_labels[real_i]);
        }
    }

    if (!found_plus_one)
    {
        SG_ERROR(
                "%s%s%s::ensure_valid(): Not a two class labeling - no positively labeled examples found\n",
                context ? context : "", context ? ": " : "", get_name());
    }

    if (!found_minus_one)
    {
        SG_ERROR(
                "%s%s%s::ensure_valid): Not a two class labeling - no negatively labeled examples found\n",
                context ? context : "", context ? ": " : "", get_name());
    }
}

ELabelType CBinaryLabels::get_label_type() const
{
    return LT_BINARY;
}

void CBinaryLabels::scores_to_probabilities(float64_t a, float64_t b)
{
    SG_DEBUG("entering CBinaryLabels::scores_to_probabilities()\n")

    REQUIRE(m_current_values.vector, "%s::scores_to_probabilities() requires "
            "values vector!\n", get_name());

    if (a==0 && b==0)
    {
        CStatistics::SigmoidParamters params=
                CStatistics::fit_sigmoid(m_current_values);
        a=params.a;
        b=params.b;
    }

    SG_DEBUG("using sigmoid: a=%f, b=%f\n", a, b)

    /* now the sigmoid is fitted, convert all values to probabilities */
    for (index_t i=0; i<m_current_values.vlen; ++i)
    {
        float64_t fApB=m_current_values[i]*a+b;
        m_current_values[i]=fApB>=0 ? CMath::exp(-fApB)/(1.0+CMath::exp(-fApB)) :
                1.0/(1+CMath::exp(fApB));
    }

    SG_DEBUG("leaving CBinaryLabels::scores_to_probabilities()\n")
}