public static void Main(string[] args)
{
NNet xor = new NNet(1)
{
Input = Vector.FromArray(new[] { 1.0, 0.0 }),
Weights = new[]
{
new Matrix().FromArray(new[, ]
{
{ 0.9, 0.2 },
{ 0.3, 0.8 },
}),
new Matrix().FromArray(new[, ]
{
{ 0.7, 0.6 },
//{ 0.3 }, //, 0.8 },
}),
}
};
xor.FeedForward();
Console.WriteLine($"XOR: {xor.Output}");
// Console.WriteLine(xor);
xor.BackPropogate(new[] { 0.9 }); // Expect 1 (becomes 0.9).
xor.FeedForward();
// Console.WriteLine(xor);
Console.WriteLine($"XOR: {xor.Output}");
// xor.FeedForward();
// Console.WriteLine($"XOR: {xor.Output}");
for (int i = 0; i < 10000; i++)
{
xor.FeedForward();
xor.BackPropogate(new[] { 0.9 }); // Expect 0 (becomes 0.1).
}
//
xor.FeedForward();
Console.WriteLine($"XOR: {xor.Output}");
NeuralNetwork nn = new NeuralNetwork(new[]
{
new Matrix().FromArray(new[, ]
{
{ 0.9, 0.2, -0.4 },
{ -0.3, 0.8, -0.9 },
{ -0.4, 0.9, 0.3 },
}),
new Matrix().FromArray(new[, ]
{
{ 0.7, -0.6, -0.2, 0.4 },
//{ 0.3 }, //, 0.8 },
}),
});
Console.WriteLine(nn.FeedForward((Vector) new VectorBuilder <Vector> {
1.0, 1.0
}.Get()));
for (int i = 0; i < 100000; i++)
{
nn.Epoch(new[] { 1.0, 1.0 }, new[] { 0.1 });
}
Console.WriteLine(nn.FeedForward((Vector) new VectorBuilder <Vector> {
1.0, 1.0
}.Get()));
Console.WriteLine(" NEURAL NET BELOW");
Console.WriteLine(nn);
// for (int i = 0; i < 10000; i++)
// {
//// nn.Epoch(new[] { 0.0, 0.0 }, new[] { 0.1 });
// nn.Epoch(new[] { 1.0, 0.0 }, new[] { 0.9 });
// nn.Epoch(new[] { 0.0, 1.0 }, new[] { 0.9 });
//// nn.Epoch(new[] { 1.0, 1.0 }, new[] { 0.1 });
// }
//
// Console.WriteLine(" ~~~~~ ");
// Console.WriteLine(nn.FeedForward((Vector) new VectorBuilder<Vector> { 0.0, 0.0 }.Get()));
// Console.WriteLine(nn.FeedForward((Vector) new VectorBuilder<Vector> { 1.0, 0.0 }.Get()));
// Console.WriteLine(nn.FeedForward((Vector) new VectorBuilder<Vector> { 0.0, 1.0 }.Get()));
// Console.WriteLine(nn.FeedForward((Vector) new VectorBuilder<Vector> { 1.0, 1.0 }.Get()));
}