/// <summary>
/// Trains the ANN that has been previously been loaded using "LoadANN()"
/// </summary>
/// <param name="?"></param>
/// <returns></returns>
public bool TrainAnn(TrainOptions options, int numTrainingSets, float[] inputs, float[] outputs, ref int terminatedAfterIter)
{
int numInputLayers = inputs.Count() / numTrainingSets;
int numOutputLayers = 1;
Console.WriteLine("Starting Training with theses parameters: " +
" Number of Training Datasets: " + numTrainingSets +
" Number of Input Layers: " + numInputLayers +
" Number of Output Layers: " + numOutputLayers);
Console.WriteLine("Inputs:");
for (int i = 0; i < inputs.Count(); i++)
{
if (i == 16)
{
Console.WriteLine();
}
Console.Write(inputs[i] + " ");
}
Console.WriteLine("Outputs:");
for (int i = 0; i < outputs.Count(); i++)
{
if (i == 1)
{
Console.WriteLine();
}
Console.Write(outputs[i] + " ");
}
int res = klu_trainAnn(options, numTrainingSets, inputs, numInputLayers, outputs, numOutputLayers, out terminatedAfterIter);
Console.WriteLine("Training finished after iteration #: " + terminatedAfterIter);
return(res == 1);
}
private static extern int klu_trainAnn(
[In, MarshalAs(UnmanagedType.LPStruct)] TrainOptions options,
int numTrainingSets,
[In, MarshalAs(UnmanagedType.LPArray)] float[] inputs,
int numInputNeurons,
[In, MarshalAs(UnmanagedType.LPArray)] float[] outputs,
int numOutputNeurons,
out int terminatedAfterIter
);
/// <summary>
/// Trains the ANN that has been previously been loaded using "LoadANN()"
/// </summary>
/// <param name="?"></param>
/// <returns></returns>
public bool TrainAnn(TrainOptions options, int numTrainingSets, float[] inputs, float[] outputs, ref int terminatedAfterIter)
{
int numInputLayers = inputs.Count() / numTrainingSets;
int numOutputLayers = 1;
Console.WriteLine("Starting Training with theses parameters: " +
" Number of Training Datasets: " + numTrainingSets +
" Number of Input Layers: " + numInputLayers +
" Number of Output Layers: " + numOutputLayers);
Console.WriteLine("Inputs:");
for (int i = 0; i < inputs.Count(); i++)
{
if (i == 16)
{
Console.WriteLine();
}
Console.Write(inputs[i] + " ");
}
Console.WriteLine("Outputs:");
for (int i = 0; i < outputs.Count(); i++)
{
if (i == 1)
{
Console.WriteLine();
}
Console.Write(outputs[i] + " ");
}
int res = klu_trainAnn(options, numTrainingSets, inputs, numInputLayers, outputs, numOutputLayers, out terminatedAfterIter);
Console.WriteLine("Training finished after iteration #: " + terminatedAfterIter);
return (res == 1);
}