Function main

examples/assignment_learning_ex.cpp:153–209

// ----------------------------------------------------------------------------------------

int main()
{
    try
    {
        // Get a small bit of training data.
        std::vector<sample_type> samples;
        std::vector<label_type> labels;
        make_data(samples, labels);


        structural_assignment_trainer<feature_extractor> trainer;
        // This is the common SVM C parameter.  Larger values encourage the
        // trainer to attempt to fit the data exactly but might overfit. 
        // In general, you determine this parameter by cross-validation.
        trainer.set_c(10);
        // This trainer can use multiple CPU cores to speed up the training.  
        // So set this to the number of available CPU cores. 
        trainer.set_num_threads(4);

        // Do the training and save the results in assigner.
        assignment_function<feature_extractor> assigner = trainer.train(samples, labels);


        // Test the assigner on our data.  The output will indicate that it makes the
        // correct associations on all samples.
        cout << "Test the learned assignment function: " << endl;
        for (unsigned long i = 0; i < samples.size(); ++i)
        {
            // Predict the assignments for the LHS and RHS in samples[i].   
            std::vector<long> predicted_assignments = assigner(samples[i]);
            cout << "true labels:      " << trans(mat(labels[i]));
            cout << "predicted labels: " << trans(mat(predicted_assignments)) << endl;
        }

        // We can also use this tool to compute the percentage of assignments predicted correctly.
        cout << "training accuracy: " << test_assignment_function(assigner, samples, labels) << endl;


        // Since testing on your training data is a really bad idea, we can also do 5-fold cross validation.
        // Happily, this also indicates that all associations were made correctly.
        randomize_samples(samples, labels);
        cout << "cv accuracy:       " << cross_validate_assignment_trainer(trainer, samples, labels, 5) << endl;



        // Finally, the assigner can be serialized to disk just like most dlib objects.
        serialize("assigner.dat") << assigner;

        // recall from disk
        deserialize("assigner.dat") >> assigner;
    }
    catch (std::exception& e)
    {
        cout << "EXCEPTION THROWN" << endl;
        cout << e.what() << endl;
    }
}