java中的多层感知器 [英] Multi layer Perceptron in java

问题描述

我想在java.please中实现MLP，指导我在这个领域的java设施。

I want to implement MLP in java.please guide me about facilities of java in this field.

推荐答案

我会先读一下主题 [ ^ ]。

看看你是否可以在 Java中找到一个例子 [ ^ ]。



使用谷歌搜索东西总是一个好主意[其他搜索引擎可用]，这需要我输入更长时间才能找到链接。

I would first read up on the subject[^].
The see if you can find an example in Java[^].

It is always a good idea to search for things using google [other search engines are available], this took me longer to type up than to find the links.

package org.neuroph.samples;



import java.util.Arrays;

import org.neuroph.core。 NeuralNetwork;

import org.neuroph.nnet.MultiLayerPerceptron;

import org.neuroph.core.data.DataSet;

import org.neuroph.core.data.DataSetRow;

import org.neuroph.util.TransferFunctionType;



/ **

*此示例显示如何创建，训练，保存和加载简单的多层感知器

* /

公共类XorMultiLayerPerceptronSample {



public static void main（String [] args）{

< br $>
//创建训练集（逻辑XOR函数）

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 [] {1}））;

trainingSet.addRow（new DataSetRow（new double [] {1,0}，new double [] {1}））;

trainingSet .addRow（new DataSetRow（new double [] {1,1}，new double [] {0}））;



//创建多层感知器

MultiLayerPerceptron myMlPerceptron = new MultiLayerPerceptron（Transf erFunctionType.TANH，2,3,1）;

//学习训练集

myMlPerceptron.learn（trainingSet）;



//测试感知器

System.out.println（测试经过训练的神经网络）;

testNeuralNetwork（myMlPerceptron，trainingSet）;



//保存训练有素的神经网络

myMlPerceptron.save（myMlPerceptron.nnet）;



//加载保存的神经网络

NeuralNetwork loadedMlPerceptron = NeuralNetwork.createFromFile（myMlPerceptron.nnet）;



//测试加载神经网络

System.out.println（测试加载神经网络）;

testNeuralNetwork（loadedMlPerceptron，trainingSet）;

< br $>
}



public static void testNeuralNetwork（NeuralNetwork nnet，DataSet testSet）{



for（DataSetRow dataRow：testSet.getRows（））{

nnet.setInput（dataRow.getInput（））;

nnet.calculate（）;

d ouble [] networkOutput = nnet.getOutput（）;

System.out.print（输入：+ Arrays.toString（dataRow.getInput（）））;

System.out.println（输出：+ Arrays.toString（networkOutput））;

}



}







}

package org.neuroph.samples;

import java.util.Arrays;
import org.neuroph.core.NeuralNetwork;
import org.neuroph.nnet.MultiLayerPerceptron;
import org.neuroph.core.data.DataSet;
import org.neuroph.core.data.DataSetRow;
import org.neuroph.util.TransferFunctionType;

/**
* This sample shows how to create, train, save and load simple Multi Layer Perceptron
*/
public class XorMultiLayerPerceptronSample {

public static void main(String[] args) {

// create training set (logical XOR 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[]{1}));
trainingSet.addRow(new DataSetRow(new double[]{1, 0}, new double[]{1}));
trainingSet.addRow(new DataSetRow(new double[]{1, 1}, new double[]{0}));

// create multi layer perceptron
MultiLayerPerceptron myMlPerceptron = new MultiLayerPerceptron(TransferFunctionType.TANH, 2, 3, 1);
// learn the training set
myMlPerceptron.learn(trainingSet);

// test perceptron
System.out.println("Testing trained neural network");
testNeuralNetwork(myMlPerceptron, trainingSet);

// save trained neural network
myMlPerceptron.save("myMlPerceptron.nnet");

// load saved neural network
NeuralNetwork loadedMlPerceptron = NeuralNetwork.createFromFile("myMlPerceptron.nnet");

// test loaded neural network
System.out.println("Testing loaded neural network");
testNeuralNetwork(loadedMlPerceptron, trainingSet);

}

public static void testNeuralNetwork(NeuralNetwork nnet, DataSet testSet) {

for(DataSetRow dataRow : testSet.getRows()) {
nnet.setInput(dataRow.getInput());
nnet.calculate();
double[ ] networkOutput = nnet.getOutput();
System.out.print("Input: " + Arrays.toString(dataRow.getInput()) );
System.out.println(" Output: " + Arrays.toString(networkOutput) );
}

}



}

这篇关于java中的多层感知器的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！