com.mycompany.neuralnetwork.NeuralNetworkShell.java Source code

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Here is the source code for com.mycompany.neuralnetwork.NeuralNetworkShell.java

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package com.mycompany.neuralnetwork;

import java.util.Random;
import weka.classifiers.Classifier;
import weka.classifiers.Evaluation;
import weka.classifiers.functions.MultilayerPerceptron;
import weka.core.Instances;
import weka.core.converters.ConverterUtils;
import weka.filters.Filter;
import weka.filters.unsupervised.attribute.Standardize;

/**
 *
 * @author Besseym
 */
public class NeuralNetworkShell {
    public static void main(String[] args) throws Exception {
        ConverterUtils.DataSource source = new ConverterUtils.DataSource("irisData.csv");
        Instances dataSet = source.getDataSet();

        Standardize standardize = new Standardize();
        standardize.setInputFormat(dataSet);
        dataSet = Filter.useFilter(dataSet, standardize);
        dataSet.setClassIndex(dataSet.numAttributes() - 1);
        dataSet.randomize(new Random(9001)); //It's over 9000!!

        int trainingSize = (int) Math.round(dataSet.numInstances() * .7);
        int testSize = dataSet.numInstances() - trainingSize;

        Instances trainingData = new Instances(dataSet, 0, trainingSize);
        Instances testData = new Instances(dataSet, trainingSize, testSize);

        //MultilayerPerceptron classifier = new MultilayerPerceptron();
        NeuralNetworkClassifier classifier = new NeuralNetworkClassifier(3, 20000, 0.1);
        classifier.buildClassifier(trainingData);

        Evaluation eval = new Evaluation(trainingData);
        eval.evaluateModel(classifier, testData);

        System.out.println(eval.toSummaryString("\nResults:\n", false));
    }
}