public ActionResult HandleCSVForm(NetworkSeed seed)
{
var stream = seed.File.InputStream;
List <StockHistory> history = parseCSV(stream);
var historyForTrain = history.GetRange(0, (int)(history.Count * 0.8));
#region hide
historyForTrain = history;
#endregion
NNPredictor predictor = new NNPredictor(historyForTrain, parameters);
var stock = new Stock
{
Name = seed.Name,
Ticker = seed.Ticker,
Data = BlobConverter <NNPredictor> .Encode(predictor)
};
db.Stocks.Add(stock);
db.SaveChanges();
var stockId = stock.Id;
db.StocksHistory.AddRange(history.Select(x => { x.StockId = stockId; return(x); }));
savePredictedStockHistory(history, stockId, predictor);
db.SaveChanges();
return(RedirectToAction("Edit"));
}
public IHttpActionResult MakePrediction(PredictionSeed seed)
{
NNPredictor predictor = BlobConverter <NNPredictor> .Decode(db.Stocks.Find(seed.id).Data);
List <StockHistory> history = new List <StockHistory>();
StockHistory firstDay = new StockHistory
{
Close = seed.day1.Close,
Volume = seed.day1.Volume
};
history.Add(firstDay);
StockHistory secondDay = new StockHistory
{
Close = seed.day2.Close,
Volume = seed.day2.Volume
};
history.Add(secondDay);
StockHistory thirdDay = new StockHistory
{
Close = seed.day3.Close,
Volume = seed.day3.Volume
};
history.Add(thirdDay);
var output = predictor.Predict(history)[0][0];
return(Ok(output));
}
private void savePredictedStockHistory(List <StockHistory> history, int id, NNPredictor predictor)
{
int size = parameters.LagWindowSize;
for (int i = 0; i < history.Count - size; i++)
{
var output = predictor.Predict(history.GetRange(i, size));
var predicted = new PredictedStockHistory
{
Date = history[i + size].Date,
Close = output[0][0],
StockId = id
};
db.PredictedStockHistories.Add(predicted);
}
}
