Accord.Tests.Neuro.RestrictedBoltzmannNetworkTest.CreateActivationNetworkTest C# (CSharp) Method

        public void CreateActivationNetworkTest()
        {
            double[][] inputs =
            {
                new double[] { 1,1,1,0,0,0 },
                new double[] { 1,0,1,0,0,0 },
                new double[] { 1,1,1,0,0,0 },
                new double[] { 0,0,1,1,1,0 },
                new double[] { 0,0,1,1,0,0 },
                new double[] { 0,0,1,1,1,0 }
            };

            double[][] outputs =
            {
                new double[] { 0 },
                new double[] { 0 },
                new double[] { 0 },
                new double[] { 1 },
                new double[] { 1 },
                new double[] { 1 },
            };

            RestrictedBoltzmannMachine network = createNetwork(inputs);

            ActivationNetwork ann = network.ToActivationNetwork(new SigmoidFunction(1), outputs: 1);

            ParallelResilientBackpropagationLearning teacher = new ParallelResilientBackpropagationLearning(ann);

            for (int i = 0; i < 100; i++)
            {
                teacher.RunEpoch(inputs, outputs);
            }

            double[] actual = new double[outputs.Length];
            for (int i = 0; i < inputs.Length; i++)
                actual[i] = ann.Compute(inputs[i])[0];

            Assert.AreEqual(0, actual[0], 1e-10);
            Assert.AreEqual(0, actual[1], 1e-10);
            Assert.AreEqual(0, actual[2], 1e-10);
            Assert.AreEqual(1, actual[3], 1e-10);
            Assert.AreEqual(1, actual[4], 1e-10);
            Assert.AreEqual(1, actual[5], 1e-10);
        }