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

        private static RestrictedBoltzmannMachine createNetwork(double[][] inputs)
        {
            RestrictedBoltzmannMachine network = new RestrictedBoltzmannMachine(6, 2);

            network.Hidden.Neurons[0].Weights[0] = 0.00461421;
            network.Hidden.Neurons[0].Weights[1] = 0.04337112;
            network.Hidden.Neurons[0].Weights[2] = -0.10839599;
            network.Hidden.Neurons[0].Weights[3] = -0.06234004;
            network.Hidden.Neurons[0].Weights[4] = -0.03017057;
            network.Hidden.Neurons[0].Weights[5] = 0.09520391;
            network.Hidden.Neurons[0].Threshold = 0;

            network.Hidden.Neurons[1].Weights[0] = 0.08263872;
            network.Hidden.Neurons[1].Weights[1] = -0.118437;
            network.Hidden.Neurons[1].Weights[2] = -0.21710971;
            network.Hidden.Neurons[1].Weights[3] = 0.02332903;
            network.Hidden.Neurons[1].Weights[4] = 0.00953116;
            network.Hidden.Neurons[1].Weights[5] = 0.09870652;
            network.Hidden.Neurons[1].Threshold = 0;

            network.Visible.Neurons[0].Threshold = 0;
            network.Visible.Neurons[1].Threshold = 0;
            network.Visible.Neurons[2].Threshold = 0;
            network.Visible.Neurons[3].Threshold = 0;
            network.Visible.Neurons[4].Threshold = 0;
            network.Visible.Neurons[5].Threshold = 0;

            network.Visible.CopyReversedWeightsFrom(network.Hidden);


            ContrastiveDivergenceLearning target = new ContrastiveDivergenceLearning(network);

            int iterations = 5000;
            double[] errors = new double[iterations];
            for (int i = 0; i < iterations; i++)
                errors[i] = target.RunEpoch(inputs);

            return network;
        }