public void Run()
{
// get iris file from resource stream
Assembly assembly = Assembly.GetExecutingAssembly();
var f = assembly.GetManifestResourceStream("HillClimbing.Resources.iris.csv");
StreamReader sr = new StreamReader(f);
// load all records into new dataset
DataSet ds = DataSet.Load(sr);
sr.Close();
Dictionary<string, int> species = ds.EncodeOneOfN(4); // encode specie names using one of n encoding
// get a list of records with data and encoded class name
List<Record> trainingData = ds.ExtractSupervised(0, 4, 4, 3);
Network net = new Network(4, 4, 2); // new RBF network
net.Randomize(); // initialize the networks state
Scorer score = new Scorer(trainingData); // new scorer
HillClimb hc = new HillClimb(net, score, 1.2, 1); // new hill climbing training algorithm
Iterate(hc, 100, 0.01); // iterate through hill climbing algorithm
QueryOneOfN(net, trainingData, species); // display ideal and actual specie names
}
public void Run()
{
// get iris file from resource stream
Assembly assembly = Assembly.GetExecutingAssembly();
var f = assembly.GetManifestResourceStream("HillClimbing.Resources.iris.csv");
StreamReader sr = new StreamReader(f);
// load all records into new dataset
DataSet ds = DataSet.Load(sr);
sr.Close();
Dictionary <string, int> species = ds.EncodeOneOfN(4); // encode specie names using one of n encoding
// get a list of records with data and encoded class name
List <Record> trainingData = ds.ExtractSupervised(0, 4, 4, 3);
Network net = new Network(4, 4, 2); // new RBF network
net.Randomize(); // initialize the networks state
Scorer score = new Scorer(trainingData); // new scorer
HillClimb hc = new HillClimb(net, score, 1.2, 1); // new hill climbing training algorithm
Iterate(hc, 100, 0.01); // iterate through hill climbing algorithm
QueryOneOfN(net, trainingData, species); // display ideal and actual specie names
}
/// <summary>
/// Iterate through a hill climbing algorithm.
/// Tries to minimize score.
/// </summary>
/// <param name="hc">Algorithm to iterate through.</param>
/// <param name="numIterations">Maximum iterations.</param>
/// <param name="minScore">Minimum score.</param>
private void Iterate(HillClimb hc, int numIterations, double minScore)
{
int iterationNumber = 0; // number of iterations
bool done = false; // is the algorithm done?
// while not done...
do {
iterationNumber++; // increase number of iterations
hc.Iteration(); // run an iteration
// if iteration reaches limit or score reaches min score
if(iterationNumber >= numIterations || hc.LastError < minScore) {
done = true; // set done = true
}
// write out iteration # and score
Console.WriteLine("Iteration #" + iterationNumber + ", Score=" + hc.LastError + " (Minimize)");
} while(!done);
}
/// <summary>
/// Iterate through a hill climbing algorithm.
/// Tries to minimize score.
/// </summary>
/// <param name="hc">Algorithm to iterate through.</param>
/// <param name="numIterations">Maximum iterations.</param>
/// <param name="minScore">Minimum score.</param>
private void Iterate(HillClimb hc, int numIterations, double minScore)
{
int iterationNumber = 0; // number of iterations
bool done = false; // is the algorithm done?
// while not done...
do
{
iterationNumber++; // increase number of iterations
hc.Iteration(); // run an iteration
// if iteration reaches limit or score reaches min score
if (iterationNumber >= numIterations || hc.LastError < minScore)
{
done = true; // set done = true
}
// write out iteration # and score
Console.WriteLine("Iteration #" + iterationNumber + ", Score=" + hc.LastError + " (Minimize)");
} while(!done);
}