public static BasicMLDataSet GetSet <T>(this ILearningScenario <T> scenario,
IList <T> dataSource)
{
double[][] input = scenario.InputParams.GetValues(dataSource);
double[][] ideal = scenario.OutputParams.GetValues(dataSource);
return(new BasicMLDataSet(input, ideal));
}
public static void Compute <T>(BasicNetwork network, ILearningScenario <T> scenario,
IList <T> dataSource)
{
var computingSet = scenario.GetSet(dataSource);
foreach (var item in computingSet)
{
var output = network.Compute(item.Input);
Console.WriteLine($"Input: {item.Input[0]}, {item.Input[1]} Ideal: {item.Ideal[0]} Actual: {output[0]}");
}
}
public static BasicNetwork Train <T>(ILearningScenario <T> scenario,
IList <T> dataSource,
BasicNetwork network = null)
{
if (network == null)
{
network = NeuralNetwork
.CreateNetwork(scenario.InputParams.Count,
scenario.OutputParams.Count);
}
BasicMLDataSet trainingSet = scenario.GetSet(dataSource);
var training = GetTraining(network, trainingSet);
int epoch = 1;
do
{
training.Iteration();
Debug.WriteLine($"Iteration No: {epoch++}, Error: {training.Error}");
}while (training.Error > scenario.MaxError || epoch < scenario.MaxIterations);
return(network);
}
