c# - 使用Accord.NET运行BackPropagation时为什么会出现OutofRangeException？

我搞砸了Accord.NET中不同的深度学习算法。我决定对我周围的光谱数据进行处理。 I PCA使用Accord的统计工具箱转换数据，以便将其减少到10个数据点。然后按照教程中的字母进行操作：

// Setup the deep belief network and initialize with random weights.
        DeepBeliefNetwork network = new DeepBeliefNetwork(transformedInputs.First().Length, 10, 10);
        new GaussianWeights(network, 0.1).Randomize();
        network.UpdateVisibleWeights();

        // Setup the learning algorithm.
        DeepBeliefNetworkLearning teacher = new DeepBeliefNetworkLearning(network)
        {
            Algorithm = (h, v, i) => new ContrastiveDivergenceLearning(h, v)
            {
                LearningRate = 0.1,
                Momentum = 0.5,
                Decay = 0.001,
            }
        };

        // Setup batches of input for learning.
        int batchCount = Math.Max(1, transformedInputs.Length / 100);
        // Create mini-batches to speed learning.
        int[] groups = Accord.Statistics.Tools.RandomGroups(transformedInputs.Length, batchCount);
        double[][][] batches = transformedInputs.Subgroups(groups);
        // Learning data for the specified layer.
        double[][][] layerData;

        // Unsupervised learning on each hidden layer, except for the output layer.
        for (int layerIndex = 0; layerIndex < network.Machines.Count - 1; layerIndex++)
        {
            teacher.LayerIndex = layerIndex;
            layerData = teacher.GetLayerInput(batches);
            for (int i = 0; i < 200; i++)
            {
                double error = teacher.RunEpoch(layerData) / transformedInputs.Length;
                if (i % 10 == 0)
                {
                    Console.WriteLine(i + ", Error = " + error);
                }
            }
        }

        // Supervised learning on entire network, to provide output classification.
        var teacher2 = new BackPropagationLearning(network)
        {
            LearningRate = 0.1,
            Momentum = 0.5
        };


        // Run supervised learning.
        for (int i = 0; i < 500; i++)
        {
            double error = teacher2.RunEpoch(transformedInputs, output: outputs);
            if (i % 10 == 0)
            {
                Console.WriteLine(i + ", Error = " + error);
            }
        }

我检查了输入的数据，输入和输出的格式都是正确的double [] []格式。我还检查了原始应用程序：https://github.com/primaryobjects/deep-learning
而且效果非常好，因此我很努力地看到，仅更改输入数据的内容就变得如此混乱。任何帮助将不胜感激。我得到的错误是：

An unhandled exception of type 'System.IndexOutOfRangeException' occurred in Accord.Neuro.dll

附加信息：索引超出了数组的范围。

最佳答案

当然，发布此问题之后，我立即意识到我的网络将必须反映输出的数量，并且该数量被设置为10。非常抱歉打扰这个出色的社区。