本文整理汇总了Java中org.neuroph.core.NeuralNetwork.save方法的典型用法代码示例。如果您正苦于以下问题：Java NeuralNetwork.save方法的具体用法？Java NeuralNetwork.save怎么用？Java NeuralNetwork.save使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类org.neuroph.core.NeuralNetwork的用法示例。
在下文中一共展示了NeuralNetwork.save方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Java代码示例。
示例1: main
import org.neuroph.core.NeuralNetwork; //导入方法依赖的package包/类
/**
* Runs this sample
*/
public static void main(String args[]) {
// create training set (logical AND function)
DataSet trainingSet = new DataSet(2, 1);
trainingSet.addRow(new DataSetRow(new double[]{0, 0}, new double[]{0}));
trainingSet.addRow(new DataSetRow(new double[]{0, 1}, new double[]{0}));
trainingSet.addRow(new DataSetRow(new double[]{1, 0}, new double[]{0}));
trainingSet.addRow(new DataSetRow(new double[]{1, 1}, new double[]{1}));
// create perceptron neural network
NeuralNetwork myPerceptron = new Perceptron(2, 1);
// learn the training set
myPerceptron.learn(trainingSet);
// test perceptron
System.out.println("Testing trained perceptron");
testNeuralNetwork(myPerceptron, trainingSet);
// save trained perceptron
myPerceptron.save("mySamplePerceptron.nnet");
// load saved neural network
NeuralNetwork loadedPerceptron = NeuralNetwork.load("mySamplePerceptron.nnet");
// test loaded neural network
System.out.println("Testing loaded perceptron");
testNeuralNetwork(loadedPerceptron, trainingSet);
}
示例2: main
import org.neuroph.core.NeuralNetwork; //导入方法依赖的package包/类
public static void main(String[] args) {
// create new perceptron network
NeuralNetwork neuralNetwork = new Perceptron(3, 1);
// create training set
DataSet trainingSet = new DataSet(3, 1);
// add training data to training set (logical OR function)
trainingSet.addRow(new DataSetRow(new double[] { 0, 0 ,0}, new double[] { 0 }));
trainingSet.addRow(new DataSetRow(new double[] { 0, 1 ,0}, new double[] { 1 }));
trainingSet.addRow(new DataSetRow(new double[] { 1, 0 ,0}, new double[] { 1 }));
trainingSet.addRow(new DataSetRow(new double[] { 1, 1 ,0}, new double[] { 1 }));
trainingSet.addRow(new DataSetRow(new double[] { 0, 0 ,1}, new double[] { 1 }));
trainingSet.addRow(new DataSetRow(new double[] { 0, 1 ,1}, new double[] { 1 }));
trainingSet.addRow(new DataSetRow(new double[] { 1, 0 ,1}, new double[] { 1 }));
trainingSet.addRow(new DataSetRow(new double[] { 1, 1 ,1}, new double[] { 1 }));
// learn the training set
neuralNetwork.learn(trainingSet);
// save the trained network into file
neuralNetwork.save("or_perceptron.nnet");
// load the saved network
NeuralNetwork neuralNetwork1 = NeuralNetwork.createFromFile("or_perceptron.nnet");
// set network input
neuralNetwork1.setInput(1, 1,1);
// calculate network
neuralNetwork1.calculate();
// get network output
double[] networkOutput = neuralNetwork1.getOutput();
System.out.println(Arrays.toString(networkOutput));
}