AIMA.Test.Core.Unit.Learning.Neural.BackPropagationTests.testFeedForwardAndBAckLoopWorks C# (CSharp) Метод

        public void testFeedForwardAndBAckLoopWorks()
        {
            // example 11.14 of Neural Network Design by Hagan, Demuth and Beale
            Matrix hiddenLayerWeightMatrix = new Matrix(2, 1);
            hiddenLayerWeightMatrix.set(0, 0, -0.27);
            hiddenLayerWeightMatrix.set(1, 0, -0.41);

            Vector hiddenLayerBiasVector = new Vector(2);
            hiddenLayerBiasVector.setValue(0, -0.48);
            hiddenLayerBiasVector.setValue(1, -0.13);

            Vector input = new Vector(1);
            input.setValue(0, 1);

            Matrix outputLayerWeightMatrix = new Matrix(1, 2);
            outputLayerWeightMatrix.set(0, 0, 0.09);
            outputLayerWeightMatrix.set(0, 1, -0.17);

            Vector outputLayerBiasVector = new Vector(1);
            outputLayerBiasVector.setValue(0, 0.48);

            Vector error = new Vector(1);
            error.setValue(0, 1.261);

            double learningRate = 0.1;
            double momentumFactor = 0.0;
            FeedForwardNeuralNetwork ffnn = new FeedForwardNeuralNetwork(
                    hiddenLayerWeightMatrix, hiddenLayerBiasVector,
                    outputLayerWeightMatrix, outputLayerBiasVector);
            ffnn.setTrainingScheme(new BackPropLearning(learningRate,
                    momentumFactor));
            ffnn.processInput(input);
            ffnn.processError(error);

            Matrix finalHiddenLayerWeights = ffnn.getHiddenLayerWeights();
            Assert.AreEqual(-0.265, finalHiddenLayerWeights.get(0, 0), 0.001);
            Assert.AreEqual(-0.419, finalHiddenLayerWeights.get(1, 0), 0.001);

            Vector hiddenLayerBias = ffnn.getHiddenLayerBias();
            Assert.AreEqual(-0.475, hiddenLayerBias.getValue(0), 0.001);
            Assert.AreEqual(-0.1399, hiddenLayerBias.getValue(1), 0.001);

            Matrix finalOutputLayerWeights = ffnn.getOutputLayerWeights();
            Assert.AreEqual(0.171, finalOutputLayerWeights.get(0, 0), 0.001);
            Assert.AreEqual(-0.0772, finalOutputLayerWeights.get(0, 1), 0.001);

            Vector outputLayerBias = ffnn.getOutputLayerBias();
            Assert.AreEqual(0.7322, outputLayerBias.getValue(0), 0.001);
        }