/// <summary>
/// Prepare a Kaggle submission for Titanic.
/// </summary>
/// <param name="dataPath">The data path.</param>
/// <param name="bestNetwork">The best network.</param>
/// <param name="cross">The cross validated data.</param>
public void Submit(string dataPath, RBFNetwork bestNetwork, CrossValidate cross)
{
String now = new DateTime().ToString("yyyyMMddhhmm");
string trainingPath = Path.Combine(dataPath, TitanicConfig.TrainingFilename);
string testPath = Path.Combine(dataPath, TitanicConfig.TestFilename);
var score = (int)(cross.Score * 10000);
string submitPath = Path.Combine(dataPath, "submit-" + now + "_" + score + ".csv");
string submitInfoPath = Path.Combine(dataPath, "submit-" + now + ".txt");
using (var file = new StreamWriter(submitInfoPath))
{
file.WriteLine("Crossvalidation stats:");
for (int i = 0; i < cross.Count; i++)
{
CrossValidateFold fold = cross.Folds[i];
file.WriteLine("Fold #" + (i + 1) + " : Score: " + fold.Score);
}
file.WriteLine("Average Score: " + cross.Score);
file.WriteLine();
file.WriteLine(String.Join(",", bestNetwork.LongTermMemory));
}
var stats = new TitanicStats();
NormalizeTitanic.Analyze(stats, trainingPath);
NormalizeTitanic.Analyze(stats, testPath);
var ids = new List <String>();
IList <BasicData> training = NormalizeTitanic.Normalize(stats, testPath, ids,
TitanicConfig.InputNormalizeLow,
TitanicConfig.InputNormalizeHigh,
TitanicConfig.PredictSurvive,
TitanicConfig.PredictPerish);
int idx = 0;
using (var streamWriter = new StreamWriter(submitPath))
using (var writer = new CsvWriter(streamWriter))
{
writer.WriteField("PassengerId");
writer.WriteField("Survived");
writer.NextRecord();
foreach (BasicData data in training)
{
double[] output = bestNetwork.ComputeRegression(data.Input);
int survived = output[0] > 0.5 ? 1 : 0;
writer.WriteField(ids[idx]);
writer.WriteField(survived);
writer.NextRecord();
idx++;
}
}
}
/// <summary>
/// Fit a RBF model to the titanic.
/// </summary>
/// <param name="dataPath">The path that contains the data file.</param>
public void Process(string dataPath)
{
string trainingPath = Path.Combine(dataPath, TitanicConfig.TrainingFilename);
string testPath = Path.Combine(dataPath, TitanicConfig.TestFilename);
IGenerateRandom rnd = new MersenneTwisterGenerateRandom();
// Generate stats on the titanic.
var stats = new TitanicStats();
NormalizeTitanic.Analyze(stats, trainingPath);
NormalizeTitanic.Analyze(stats, testPath);
// Get the training data for the titanic.
IList <BasicData> training = NormalizeTitanic.Normalize(stats, trainingPath, null,
TitanicConfig.InputNormalizeLow,
TitanicConfig.InputNormalizeHigh,
TitanicConfig.PredictSurvive,
TitanicConfig.PredictPerish);
// Fold the data for cross validation.
_cross = new CrossValidate(TitanicConfig.FoldCount, training, rnd);
// Train each of the folds.
for (int k = 0; k < _cross.Count; k++)
{
Console.WriteLine("Cross validation fold #" + (k + 1) + "/" + _cross.Count);
TrainFold(k, _cross.Folds[k]);
}
// Show the cross validation summary.
Console.WriteLine("Crossvalidation summary:");
int kk = 1;
foreach (CrossValidateFold fold in _cross.Folds)
{
Console.WriteLine("Fold #" + kk + ": " + fold.Score);
kk++;
}
Console.WriteLine("Final, crossvalidated score:" + _cross.Score);
}