bagging.cpp

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#include <assert.h>
#include "bagging.h"

REGISTER_CREATOR(lemga::Bagging);

namespace lemga {

Bagging::Bagging (UINT max) : Aggregating() {
    set_max_models(max);
}

Output Bagging::operator() (const Input& x) const {
    assert(n_in_agg > 0 && n_in_agg <= size());

    Output y(_n_out, 0);

    for (UINT i = 0; i < n_in_agg; ++i) {
        assert(lm[i] != 0);
        Output yi = (*lm[i])(x);
        for (UINT j = 0; j < _n_out; ++j)
            y[j] += (yi[j] > 0)? 1 : -1;
    }
    for (UINT j = 0; j < _n_out; ++j)
        y[j] /= n_in_agg;

    return y;
}

REAL Bagging::train () {
    assert(n_in_agg == 0 && empty());

    REAL err = 0;
    for (UINT i = 0; i < max_n_model; ++i) {
#if VERBOSE_OUTPUT
        std::cout << "=== " << id() << " #" << i+1 << " / "
                  << max_n_model << " ===\n";
#endif
        assert(lm_base != 0);
        LearnModel *p = lm_base->clone();
        p->set_train_data(ptd->random_sample(*ptw, n_samples));
        p->initialize();
        err += p->train();
        lm.push_back(p);
    }
    n_in_agg = max_n_model;

    return (err / n_in_agg);
}

} // namespace lemga

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