/// <summary>
/// Trains a new player network based on available database data and returns the most accurate network, previous or new.
/// </summary>
/// <param name="playerId"></param>
/// <param name="currentHandId"></param>
/// <param name="currentNetwork"></param>
/// <returns></returns>
protected PAPNetworkContainer trainPlayerNetwork(long playerId, long currentHandId, PAPNetworkContainer previousNetwork, long startingHandId, int maxTrainingActions)
{
DateTime startTime = DateTime.Now;
PAPNetworkContainer returnNetworkContainer;
PokerPlayerNNModelv1 playerPredictionNNModel = new PokerPlayerNNModelv1();
playerPredictionNNModel.populatePlayActions(playerId, maxTrainingActions, startingHandId);
playerPredictionNNModel.SuffleDataSource();
if (playerPredictionNNModel.DataSourceCount < minActionsRequiredForNetwork)
{
return(previousNetwork);
}
playerPredictionNNModel.createNetwork();
playerPredictionNNModel.createTrainingSets();
playerPredictionNNModel.trainNetwork();
playerPredictionNNModel.createTestingSets();
BasicNetwork newPlayerNetwork = playerPredictionNNModel.Network;
decimal newNetworkAccuracy = playerPredictionNNModel.getNetworkAccuracy();
//We need to get the accuracy of the previous network on the new data so that it is a fair comparison
playerPredictionNNModel.Network = previousNetwork.PlayerNetworkPool.BaseNetwork;
decimal previousNetworkAccuracy = playerPredictionNNModel.getNetworkAccuracy();
if (newNetworkAccuracy > previousNetworkAccuracy)
{
previousNetwork.UpdateNetwork(newPlayerNetwork, newNetworkAccuracy, playerPredictionNNModel.DataSourceCount, currentHandId);
}
else
{
//Regardless of whether we replace network/accuracy, we reset the trainingActions and mostRecentHandId
previousNetwork.UpdateNetwork(previousNetwork.PlayerNetworkPool.BaseNetwork, previousNetworkAccuracy, playerPredictionNNModel.DataSourceCount, currentHandId);
}
returnNetworkContainer = previousNetwork;
//SerializeObject.Save(PAP_STORE + playerId.ToString() + ".PAPdat", returnNetworkContainer);
returnNetworkContainer.SavePAPContainer(PAP_STORE, playerId.ToString());
return(returnNetworkContainer);
}
public void Go3()
{
Console.WriteLine("Let's get this show on the road!!");
long[] allPlayerIds = new long[0];
//Todo - Add players to allPlayerIds
//Get all of the playerActions
Console.WriteLine("Testing new network accuracy for {0} players.", allPlayerIds.Length);
for (int i = 0; i < allPlayerIds.Length; i++)
{
try
{
PokerPlayerNNModelv1 playerPrediction = new PokerPlayerNNModelv1();
playerPrediction.populatePlayActions(allPlayerIds[i], 10000, 0);
playerPrediction.SuffleDataSource();
//playerPrediction.createNetwork();
//playerPrediction.createTrainingSets();
//playerPrediction.trainNetwork();
playerPrediction.Network = NNLoadSave.loadNetwork("generalPlayer.eNN", "");
Console.WriteLine("... data loaded for player index {0} ({1}). {2} actions added.", i, allPlayerIds[i], playerPrediction.NeuralNetDataSource.Count);
//playerPrediction.SaveNNDataSource("allPlayerPAPData.csv");
playerPrediction.createTestingSets();
decimal accuracy = playerPrediction.getNetworkAccuracy();
Console.WriteLine("PlayerId:{0} Predicted {1}% Of Actions Correctly.", allPlayerIds[i], Math.Round(accuracy, 1));
using (System.IO.StreamWriter sw = new System.IO.StreamWriter("accuracy.csv", true))
sw.WriteLine(allPlayerIds[i] + ", " + Math.Round(accuracy, 1));
}
catch (Exception ex)
{
Console.WriteLine("Meh - Error on playerId {0}.", allPlayerIds[i]);
using (System.IO.StreamWriter sw = new System.IO.StreamWriter("errors.txt", true))
sw.WriteLine(ex.ToString());
}
}
//NNLoadSave.saveNetwork(playerPrediction.Network, "generalPlayer.eNN", "");
Console.WriteLine("... completed.");
Console.ReadKey();
}
public void Go2()
{
Console.WriteLine("Let's get this show on the road!!");
//Get all of the playerActions
for (int i = 0; i < 20; i++)
{
PokerPlayerNNModelv1 playerPrediction = new PokerPlayerNNModelv1();
playerPrediction.LoadNNDatasource("allPlayerPAPData.csv", PokerPlayerNNModelv1.Input_Neurons, PokerPlayerNNModelv1.Output_Neurons);
playerPrediction.SuffleDataSource();
playerPrediction.createNetwork();
playerPrediction.createTrainingSets();
playerPrediction.trainNetwork();
playerPrediction.createTestingSets();
decimal accuracy = playerPrediction.getNetworkAccuracy();
Console.WriteLine("Achieved {0}% accuracy.", accuracy);
NNLoadSave.saveNetwork(playerPrediction.Network, accuracy.ToString() + "_generalPlayer.eNN", "");
}
Console.WriteLine("... completed.");
Console.ReadKey();
}