我使用 encog 库实现了一个神经网络，如下所示，

MLDataSet trainingSet = new BasicMLDataSet(XOR_INPUT, XOR_IDEAL);    final Propagation  train =  new Backpropagation(network, trainingSet);    int epoch = 1;    do {        train.iteration();        System.out.println("Epoch #" + epoch +                 " Error:" + train.getError());                epoch++;    } while (train.getError() < 0.009);    double e = network.calculateError(trainingSet);    System.out.println("Network trained to error :" + e);    System.out.println("Saving Network");    EncogDirectoryPersistence.saveObject(new File(FILENAME), network);}public void loadAndEvaluate(){    System.out.println("Loading Network");    BasicNetwork network = (BasicNetwork) EncogDirectoryPersistence.loadObject(new File(FILENAME));    BasicMLDataSet trainingSet = new BasicMLDataSet(XOR_INPUT,XOR_IDEAL);    double e = network.calculateError(trainingSet);    System.out.println("Loaded network's error is (should be the same as above ):" + e);}

这会输出错误信息。但我想用自定义数据进行测试，并检查一组数据的输出是否正确

回答：

我看到你正在参考一个持久化示例。要获取某些输入的输出，请使用“compute”函数。例如：

    double[] output = new double[1];    network.compute(new double[]{1.0, 1.0}, output);    System.out.println("Network output: " + output[0] + " (should be close to 0.0)");

这里是 Java 用户指南。非常有帮助。