/// <summary>
/// Train the network, using the specified training algorithm, and send the
/// output to the console.
/// </summary>
/// <param name="train">The training method to use.</param>
/// <param name="network">The network to train.</param>
/// <param name="trainingSet">The training set.</param>
/// <param name="minutes">The number of minutes to train for.</param>
public static void TrainConsole(ITrain train,
BasicNetwork network, INeuralDataSet trainingSet,
int minutes)
{
int epoch = 1;
long remaining;
Console.WriteLine("Beginning training...");
long start = Environment.TickCount;
do
{
train.Iteration();
long current = Environment.TickCount;
long elapsed = (current - start) / 1000;
remaining = minutes - elapsed / 60;
Console.WriteLine("Iteration #" + Format.FormatInteger(epoch)
+ " Error:" + Format.FormatPercent(train.Error)
+ " elapsed time = " + Format.FormatTimeSpan((int)elapsed)
+ " time left = "
+ Format.FormatTimeSpan((int)remaining * 60));
epoch++;
} while (remaining > 0 && !train.TrainingDone);
train.FinishTraining();
}
/// <summary>
/// Train to a specific error, using the specified training method, send the
/// output to the console.
/// </summary>
/// <param name="train">The training method.</param>
/// <param name="trainingSet">The training set to use.</param>
/// <param name="error">The desired error level.</param>
public static void TrainToError(ITrain train,
INeuralDataSet trainingSet,
double error)
{
int epoch = 1;
Console.WriteLine("Beginning training...");
do
{
train.Iteration();
Console.WriteLine("Iteration #" + Format.FormatInteger(epoch)
+ " Error:" + Format.FormatPercent(train.Error)
+ " Target Error: " + Format.FormatPercent(error));
epoch++;
} while (train.Error > error && !train.TrainingDone);
train.FinishTraining();
}
/// <summary>
/// Train to a specific error, using the specified training method, send the
/// output to the console.
/// </summary>
/// <param name="train">The training method.</param>
/// <param name="trainingSet">The training set to use.</param>
/// <param name="error">The desired error level.</param>
public static void TrainToError(ITrain train,
INeuralDataSet trainingSet,
double error)
{
int epoch = 1;
Console.WriteLine("Beginning training...");
do
{
train.Iteration();
Console.WriteLine("Iteration #" + Format.FormatInteger(epoch)
+ " Error:" + Format.FormatPercent(train.Error)
+ " Target Error: " + Format.FormatPercent(error));
epoch++;
} while (train.Error > error && !train.TrainingDone);
train.FinishTraining();
}
/// <summary>
/// Train the network, using the specified training algorithm, and send the
/// output to the console.
/// </summary>
/// <param name="train">The training method to use.</param>
/// <param name="network">The network to train.</param>
/// <param name="trainingSet">The training set.</param>
/// <param name="minutes">The number of minutes to train for.</param>
public static void TrainConsole(ITrain train,
BasicNetwork network, INeuralDataSet trainingSet,
int minutes)
{
int epoch = 1;
long remaining;
Console.WriteLine("Beginning training...");
long start = Environment.TickCount;
do
{
train.Iteration();
long current = Environment.TickCount;
long elapsed = (current - start) / 1000;
remaining = minutes - elapsed / 60;
Console.WriteLine("Iteration #" + Format.FormatInteger(epoch)
+ " Error:" + Format.FormatPercent(train.Error)
+ " elapsed time = " + Format.FormatTimeSpan((int)elapsed)
+ " time left = "
+ Format.FormatTimeSpan((int)remaining * 60));
epoch++;
} while (remaining > 0 && !train.TrainingDone);
train.FinishTraining();
}
