// 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); }