public void AutoTeaching(BackPropagationLearning _teacher)
 {
     for (int i = 0; i < 100000; i++)
     {
         double   pacmanLength = R.Next(800);
         double   AlphaSine    = R.NextDouble();
         double   ghostLength  = R.Next(600);
         double   BetaSine     = R.NextDouble();
         double[] Inputs       = { pacmanLength, AlphaSine, ghostLength, BetaSine };
         Console.Write("[T] Inputs >> ");
         for (int j = 0; j < Inputs.Length; j++)
         {
             Console.Write(Inputs[j] + " ");
         }
         Console.WriteLine();
         double[] Outputs = { BetaSine };
         Console.Write("[T] Outputs >> ");
         for (int j = 0; j < Outputs.Length; j++)
         {
             Console.Write(Outputs[j] + " ");
         }
         Console.WriteLine();
         for (int j = 0; j < 2; j++)
         {
             _teacher.Teach(Inputs, Outputs);
             double[] Test = _teacher.Launch(Inputs);
             Console.Write("[T] Out >> ");
             for (int k = 0; k < Test.Length; k++)
             {
                 Console.Write(Test[k] + " ");
             }
             Console.WriteLine();
         }
     }
 }
Example #2
0
        public OddTest()
        {
            Console.WriteLine("Welcome to Neural Odd Test Example");
            FeedForwardNetwork      network = new FeedForwardNetwork(new SigmoidFunction(), 1, 10, 1);
            BackPropagationLearning teacher = new BackPropagationLearning(network);

            teacher.LearningRate = 0.1;
            Random R = new Random(Environment.TickCount);

            Console.WriteLine("Training...");
            for (int i = 0; i < 1000; i++)
            {
                Console.Write("[T] Input >> ");
                int Input = R.Next(1024);
                Console.WriteLine(Input);
                teacher.Teach(Binary(Input), (Input % 2 == 0) ? (new double[] { 0 }) : (new double[] { 1 }));
                Console.Write("[T] Output >> ");
                Console.WriteLine(network.Launch(Binary(Input))[0].ToString());
            }
            Console.WriteLine("Examing...");
            Console.Write("[E] Input >> ");
            string userString = Console.ReadLine();

            while (userString != "stop")
            {
                int Number = int.Parse(userString.Split(' ')[0]);
                Console.Write("[E] Output >> ");
                Print(network.Launch(Binary(Number)));
                Console.Write("[E] Input >> ");
                userString = Console.ReadLine();
            }
            Console.WriteLine();
        }
        public void ManualTeaching(BackPropagationLearning _teacher)
        {
            Console.Write("[T] Inputs >> ");
            string userString = Console.ReadLine();

            while (userString != "stop")
            {
                double[] Inputs = ParseDoubles(userString);
                Console.Write("[T] Outputs >> ");
                userString = Console.ReadLine();
                double[] Outputs = ParseDoubles(userString);
                for (int i = 0; i < 5; i++)
                {
                    _teacher.Teach(Inputs, Outputs);
                }
                Console.Write("[T] Inputs >> ");
                userString = Console.ReadLine();
            }
        }