examples/learnAdd.cpp

Show how to train a network that performs sums between two real numbers. The training XML is built from scratch, then saved to a file, then the network is initialized using that XML file, trained, and the resulting trained network is saved to adder.net. Then, you should take a look at doAdd.cpp to see how to use that file to use the network.

#include <iostream>
#include <fstream>
#include <ctime>
#include <neural++.hpp>

using namespace std;
using namespace neuralpp;

int main()  {
        int id = 0;
        string xml;
        time_t t1, t2;

        // Create the neural network. The network is going to have
        // => 2 neurons for the input layer
        // => 2 neurons for the hidden layer
        // => 1 neuron  for the output layer
        // => a learning rate == 0.005 (just get it doing some tests until satisfied)
        // => 1000 learning steps (i.e. the network will be ready after 1000 training steps to adjust the synaptical weights
        // => 0.1 as neural threshold (the threshold above which a neuron activates)
        NeuralNet net(2, 2, 1, 0.005, 1000, 0.1);

        // Initialize a training XML as a string in 'xml'
        NeuralNet::initXML(xml);

        // Build some training sets for the XML. The format is:
        // "input1,input2,...,inputn;output1,output2,...,outputn
        // The 'id' variable is passed as reference, starting from 0,
        // and it's used to enumerate the sets in the XML file.
        xml += NeuralNet::XMLFromSet(id, "2,3;5");
        xml += NeuralNet::XMLFromSet(id, "3,2;5");
        xml += NeuralNet::XMLFromSet(id, "6,2;8");
        xml += NeuralNet::XMLFromSet(id, "2,2;4");
        xml += NeuralNet::XMLFromSet(id, "1,2;3");
        xml += NeuralNet::XMLFromSet(id, "-1,-2;-3");
        xml += NeuralNet::XMLFromSet(id, "8,9;17");
        xml += NeuralNet::XMLFromSet(id, "10,10;20");
        NeuralNet::closeXML(xml);

        // Save the XML string just created to a file
        ofstream out("adder.xml");
        out << xml;
        out.close();
        cout << "Training file adder.xml has been written\n";

        // Start the training from the XML file
        t1 = time(NULL);
        cout << "Training in progress - This may take a while...\n";
        net.train("adder.xml", NeuralNet::file);
        t2 = time(NULL);

        // Save the trained network to a binary file, that can be reloaded from any
        // application that is going to use that network
        net.save("adder.net");
        cout << "Network trained in " << (t2-t1) << " seconds. You can use adder.net file now to load this network\n";
        return 0;
}