testsvm.cpp

C＋＋编写的机器学习算法 Lemga is a C++ package which consists of classes for several learning models and gener

/* $Id: testsvm.cpp 2501 2005-11-14 07:10:45Z ling $ */

#include <iostream>
#include <fstream>
#include <lemga/svm.h>

int main (unsigned int argc, char* argv[]) {
    if (argc < 4) {
        std::cerr << "Usage: " << argv[0] << " datafile n_train n_test"
                  << "\n";
        return -1;
    }

    /* open data file */
    std::ifstream fd(argv[1]);
    if (!fd.is_open()) {
        std::cerr << argv[0] << ": data file ("
                  << argv[1] << ") open error\n";
        return -2;
    }

    /* load training and test data */
    lemga::pDataSet trd = lemga::load_data(fd, atoi(argv[2]));
    lemga::pDataSet ted = lemga::load_data(fd, atoi(argv[3]));
    std::cout << trd->size() << " training samples and "
              << ted->size() << " test samples loaded\n";
    fd.close();

    /* train SVM */
    lemga::kernel::RBF kernel(0.5);
    lemga::SVM svm(kernel);
    svm.set_train_data(trd);
    svm.set_C(10);
    svm.train();
    std::cout << "Total " << svm.n_support_vectors() << " support vectors."
              << " Please check with svm_train() output above.\n";

    /* test SVM */
    double tre = 0, tee = 0;
    for (UINT i = 0; i < trd->size(); ++i)
        tre += (svm(trd->x(i))[0] != trd->y(i)[0]);
    for (UINT i = 0; i < ted->size(); ++i)
        tee += (svm(ted->x(i))[0] != ted->y(i)[0]);
    std::cout << "training error: " << tre / trd->size()
              << ", test error: " << tee / ted->size() << "\n";

    return 0;
}