public Tuple <double, double> Forward(JumpyReflexData data)
{
i++;
// forward a random data point through the network
//var x = new Volume(new[] { 0.3, -0.5 }, new Shape(2));
if (i == 2)
{
}
var prob = Net.Forward(new Volume(data.Features, new Shape(TrainerConfig.InputNodesCount))).Get(0);
var prob2 = Net.Forward(new Volume(data.Features, new Shape(TrainerConfig.InputNodesCount))).Get(1);
return(new Tuple <double, double>(prob, prob2));
}
private List <JumpyReflexData> GenerateTrainData()
{
var trainData = new List <JumpyReflexData>();
Random r1 = new Random(DateTime.Now.Second);
Random r2 = new Random();
for (var i = 0; i < 1000; i++)
{
var first = r1.Next(0, 9);
var second = r2.Next(0, 9);
var temp = new JumpyReflexData {
Features = new[] { 0.0, 1, 0, 0, 0, 0, 0, 0, 0, 0 }, Jump = false
};
temp.Features[first] = 1.0;
temp.Features[second] = 1.0;
if ((first < 4 && first > 1) || (second < 4 && second > 1))
{
temp.Jump = true;
}
trainData.Add(temp);
}
return(trainData);
}
