// LISTEX COMMAND
public void ListExs()
{
string result = examples.ShowFileList();
if (result.Length > 0)
{
PrintClass.PrintLine(result);
}
}
// CLEAR EXAMPLES
public string ClearExamples()
{
Examples tmpExamples = Examples.Init();
if (tmpExamples.SayExamplesNum() == 0)
{
return("\n-> Error clearing examples - no examples exist.");
}
tmpExamples.ClearExamples();
PrintClass.PrintLine("\n-> Training and testing examples lists cleared - no examples exist any more.");
return("");
}
/// <summary>
/// Prints layer parameters (coefficients and biases) using PrintClass
/// </summary>
public void ShowParams(bool showDetails)
{
PrintClass.PrintLine(" Neurons number: " + neuronDeltas.Length);
PrintClass.PrintLine(" Inputs number: " + coeffs[0].Length);
PrintClass.PrintLine(" Activation function type: " + AFType.ToString().Remove(AFType.ToString().IndexOf("AFType")));
if (showDetails)
{
string tmpString;
for (int i = 0; i < neuronDeltas.Length; i++)
{
PrintClass.PrintLine("\n - Neuron " + i.ToString() + ": bias " + biases[i] + ", coefficients :");
tmpString = " ";
for (int j = 0; j < coeffs[i].Length; j++)
{
tmpString += coeffs[i][j].ToString() + " ";
}
PrintClass.PrintLine(tmpString);
}
}
}
// COST EXAMPLES
public string Cost()
{
if (network == null)
{
return("\n-> Error calculating cost - no network exists.");
}
if (!network.examples.ExamplesExist())
{
return("\n-> Error calculating cost - no examples exists.");
}
string result = network.CalcAllCost(out float cost, true);
if (result.Length > 0)
{
return(result);
}
PrintClass.PrintLine("\n-> Total cost for existing " + network.examples.SayExamplesNum().ToString() + " examples is: " + cost.ToString() + ".");
return("");
}
// HELP MESSAGE
public void Help()
{
PrintClass.PrintLine(helpMessage);
}
