public static MarketMLDataSet GrabData(string newfileLoad)
{
IMarketLoader loader = new CSVFileLoader();//CSVLoader();
loader.GetFile(newfileLoad);
var result = new MarketMLDataSet(loader,
Config.INPUT_WINDOW, Config.PREDICT_WINDOW);
// var desc = new MarketDataDescription(Config.TICKER,
// MarketDataType.Close, true, true);
var desc = new MarketDataDescription(Config.TICKER,
MarketDataType.Close, TemporalDataDescription.Type.PercentChange, true, true);
result.AddDescription(desc);
var begin = DateTime.ParseExact("29.05.2005", "dd.MM.yyyy", CultureInfo.CurrentCulture); // begin 30 days ago
var end = DateTime.ParseExact("22.07.2005", "dd.MM.yyyy", CultureInfo.CurrentCulture); // begin 30 days ago
begin = begin.AddDays(Config.DAYS_OFFSET).AddDays(Config.TEST_OFFSET);
end = end.AddDays(Config.DAYS_OFFSET).AddDays(Config.TEST_OFFSET).AddDays(Config.TEST_STRATCH);
result.Load(begin, end);
result.Generate();
return(result);
}
public static void Generate(FileInfo dataDir)
{
IMarketLoader loader = new CSVFileLoader();
CSVFileLoader.LoadedFile = "D:\\losev\\test\\1.csv";
var market = new MarketMLDataSet(loader,
Config.INPUT_WINDOW, Config.PREDICT_WINDOW);
var desc = new MarketDataDescription(
Config.TICKER, MarketDataType.Close, true, true);
market.AddDescription(desc);
var end = new DateTime(2006, 4, 13); // end today
var begin = end.AddYears(-2); // begin 30 days ago
// Gather training data for the last 2 years, stopping 60 days short of today.
// The 60 days will be used to evaluate prediction.
//begin = begin.AddDays(-460);
//end = end.AddDays(-60);
//begin = begin.AddYears(-2);
market.Load(begin, end);
market.Generate();
EncogUtility.SaveEGB(FileUtil.CombinePath(dataDir, Config.TRAINING_FILE), market);
// create a network
BasicNetwork network = EncogUtility.SimpleFeedForward(
market.InputSize,
Config.HIDDEN1_COUNT,
Config.HIDDEN2_COUNT,
market.IdealSize,
true);
// save the network and the training
EncogDirectoryPersistence.SaveObject(FileUtil.CombinePath(dataDir, Config.NETWORK_FILE), network);
}
