static void TestNeuralNetworks()
{
SimpleNeuralNetwork brain = new SimpleNeuralNetwork(2, 25, 1,
ActivationFunctions.Sigmoid, ActivationFunctions.Sigmoid,
ActivationFunctions.Derivatives.Sigmoid, ActivationFunctions.Derivatives.Sigmoid)
{
AddBias = true,
LearningRate = 0.01f,
};
/*// XOR TRAINING
* Dictionary<float[], float[]> trainingData = new Dictionary<float[], float[]>();
* trainingData.Add(new float[] { 0, 0 }, new float[] { 0, });
* trainingData.Add(new float[] { 0, 1 }, new float[] { 1, });
* trainingData.Add(new float[] { 1, 0 }, new float[] { 1, });
* trainingData.Add(new float[] { 1, 1 }, new float[] { 0, });
*
* for (int i = 0; i < 100000; i++)
* {
* var ctd = trainingData.ElementAt(RandomGenerator.GetInt(trainingData.Count));
* brain.Backpropagation(ctd.Key, ctd.Value);
* }
* WriteLine("Training end!");
*
*
* Get(0, 0);
* Get(0, 1);
* Get(1, 0);
* Get(1, 1);
*/
Dictionary <float[], float[]> trainingData = new Dictionary <float[], float[]>();
trainingData.Add(new float[] { 0, 0.0f }, new float[] { 0.0f, });
trainingData.Add(new float[] { 0, 0.1f }, new float[] { 0.1f, });
trainingData.Add(new float[] { 0, 0.2f }, new float[] { 0.2f, });
trainingData.Add(new float[] { 0, 0.3f }, new float[] { 0.3f, });
trainingData.Add(new float[] { 0, 0.4f }, new float[] { 0.4f, });
trainingData.Add(new float[] { 0, 0.5f }, new float[] { 0.5f, });
trainingData.Add(new float[] { 0, 0.6f }, new float[] { 0.6f, });
trainingData.Add(new float[] { 0, 0.7f }, new float[] { 0.7f, });
trainingData.Add(new float[] { 0, 0.8f }, new float[] { 0.8f, });
trainingData.Add(new float[] { 0, 0.9f }, new float[] { 0.9f, });
trainingData.Add(new float[] { 0, 1.0f }, new float[] { 1.0f, });
int length = trainingData.Count;
for (int i = 0; i < 100000; i++)
{
var ctd = trainingData.ElementAt(RandomGenerator.GetInt(length));
brain.Backpropagation(ctd.Key, ctd.Value);
}
WriteLine("Training end!");
WriteLine();
WriteLine("0.0");
Get(0, 0.0f);
WriteLine("0.2");
Get(0, 0.2f);
WriteLine("0.4");
Get(0, 0.4f);
WriteLine("0.6");
Get(0, 0.6f);
WriteLine("0.8");
Get(0, 0.8f);
void Get(float x0, float x1)
{
float[] output = brain.Feedforward(new float[] { x0, x1 });
WriteLine(Math.Round(output[0], 1));
WriteLine();
}
}