Multi layer Perceptron in java

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Java

artificial-intelligence

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

Posted 26-Jun-11 20:14pm

setareh51

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Nagy Vilmos · Answer 1 · 2011-06-26T22:42:00

Solution 1

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.

Posted 26-Jun-11 22:42pm

Nagy Vilmos

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Member 11606630 4-May-15 11:18am

I found only advertise but I can't find code here for multilayer perceptron in java please clarify

Member 11961175 · Answer 2 · 2016-02-01T19:17:00

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) );
}

}

}