public ActionResult RunModel(string connectionId)
{
try
{
if (!string.IsNullOrEmpty(connectionId))
{
//Get the raw data
Functions.SendProgress(connectionId, "Loading Data.", false);
var rawData = NetworkFactory.GetInputData();
var ideals = NetworkFactory.GetIdealValues();
Functions.SendProgress(connectionId, "Loading Complete.", false);
Functions.SendProgress(connectionId, "Formatting Data.", false);
//Format the data so it can be used in a neural network - all columns will have a value between 0-1 (floating point)
var formattedData = NetworkFactory.FormatInputValues(rawData);
Functions.SendProgress(connectionId, "Formatting Complete.", false);
Functions.SendProgress(connectionId, "Creating Network.", false);
//Create Network
var network = NetworkFactory.CreateNetwork(formattedData, ideals, 40);
Functions.SendProgress(connectionId, "Network Created.", false);
Functions.SendProgress(connectionId, "Training Network.", false);
//Train network
var trainedNetwork = NetworkFactory.TrainNetwork(network, formattedData, ideals, 20000,
0.001, connectionId, Functions.SendProgress);
Functions.SendProgress(connectionId, "Training Complete.", false);
Functions.SendProgress(connectionId, "Testing Network.", false);
//Finally test the network
NetworkFactory.TestNetwork(network, formattedData, ideals, connectionId, Functions.SendProgress);
Functions.SendProgress(connectionId, "Testing Complete.", false);
//Return status
network = null;
trainedNetwork = null;
return(new JsonResult()
{
Data = new { Status = "Success", Message = "Complete" },
JsonRequestBehavior = JsonRequestBehavior.DenyGet
});
}
throw new Exception("Empty Connection ID");
}
catch (Exception ex)
{
return(new JsonResult()
{
Data = new { Status = "Failure", Message = "Error running model" },
JsonRequestBehavior = JsonRequestBehavior.DenyGet
});
}
}
public static void RunANN()
{
//Get the raw data
var rawData = NetworkFactory.GetInputData();
var ideals = NetworkFactory.GetIdealValues();
//Format the data so it can be used in a neural network - all columns will have a value between 0-1 (floating point)
var formattedData = NetworkFactory.FormatInputValues(rawData);
//Create Network
var network = NetworkFactory.CreateNetwork(formattedData, ideals, 40);
//Train network
var trainedNetwork = NetworkFactory.TrainNetwork(network, formattedData, ideals, 20000, 0.001, string.Empty, OutputEpoch);
//Finally test the network
NetworkFactory.TestNetwork(network, formattedData, ideals, string.Empty);
}