Java tutorial
/* * To change this license header, choose License Headers in Project Properties. * To change this template file, choose Tools | Templates * and open the template in the editor. */ package edu.packt.neuralnet.som; import java.awt.Color; import java.awt.Paint; import org.jfree.chart.ChartFrame; import edu.packt.neuralnet.chart.Chart; import edu.packt.neuralnet.data.NeuralDataSet; import edu.packt.neuralnet.init.UniformInitialization; import edu.packt.neuralnet.learn.LearningAlgorithm; import edu.packt.neuralnet.math.RandomNumberGenerator; import java.awt.Color; import java.awt.Paint; import java.util.HashSet; import java.util.Set; import org.jfree.chart.ChartFrame; /** * * @author fab */ public class Kohonen0DTest { public static void main(String[] args) { RandomNumberGenerator.seed = 0; int numberOfInputs = 2; int numberOfNeurons = 10; int numberOfPoints = 100; double[][] rndDataSet = RandomNumberGenerator.GenerateMatrixBetween(numberOfPoints, numberOfInputs, -10.0, 10.0); Kohonen kn0 = new Kohonen(numberOfInputs, numberOfNeurons, new UniformInitialization(-1.0, 1.0), 0); NeuralDataSet neuralDataSet = new NeuralDataSet(rndDataSet, 2); CompetitiveLearning complrn = new CompetitiveLearning(kn0, neuralDataSet, LearningAlgorithm.LearningMode.ONLINE); complrn.show2DData = true; complrn.printTraining = true; complrn.setLearningRate(0.003); complrn.setMaxEpochs(10000); complrn.setReferenceEpoch(3000); try { String[] seriesNames = { "Training Data" }; Paint[] seriesColor = { Color.WHITE }; Chart chart = new Chart("Training", rndDataSet, seriesNames, 0, seriesColor); ChartFrame frame = new ChartFrame("Training", chart.scatterPlot("X", "Y")); frame.pack(); frame.setVisible(true); //System.in.read(); complrn.setPlot2DFrame(frame); complrn.showPlot2DData(); //System.in.read(); complrn.train(); } catch (Exception ne) { } } }