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 main; import FeedForwardNeuralNetwork.FeedForwardNeuralNetworkAlgorithm; import FeedForwardNeuralNetwork.Neuron; import java.io.BufferedReader; import java.io.FileReader; import weka.core.Instances; /** * * @author user-ari */ public class coba { public static void main(String[] args) throws Exception { BufferedReader breader = null; breader = new BufferedReader(new FileReader("src/main/Team.arff")); Instances inputTrain = new Instances(breader); inputTrain.setClassIndex(inputTrain.numAttributes() - 1); breader.close(); FeedForwardNeuralNetworkAlgorithm FFNN = new FeedForwardNeuralNetworkAlgorithm(inputTrain); FFNN.buildModel(1, 5); FFNN.printModel(); FFNN.printAllWeights(); double[] arr = inputTrain.get(60).toDoubleArray(); FFNN.setInputLayer(arr); FFNN.determineOutput(inputTrain.get(60)); System.out.println(FFNN.getClassOutputValues()); FFNN.updateModel(inputTrain.get(60)); FFNN.printModel(); FFNN.printAllWeights(); System.out.println("Class : " + FFNN.getClassOutputValues()); System.out.println("\nupdate again!!!!\n"); FFNN.clearModel(); arr = null; arr = inputTrain.get(61).toDoubleArray(); FFNN.setInputLayer(arr); FFNN.determineOutput(inputTrain.get(61)); FFNN.updateModel(inputTrain.get(61)); FFNN.printModel(); FFNN.printAllWeights(); System.out.println("Class : " + FFNN.getClassOutputValues()); System.out.println("\nupdate again!!!!\n"); FFNN.clearModel(); arr = null; arr = inputTrain.get(62).toDoubleArray(); FFNN.setInputLayer(arr); FFNN.determineOutput(inputTrain.get(62)); FFNN.updateModel(inputTrain.get(62)); FFNN.printModel(); FFNN.printAllWeights(); System.out.println("Class : " + FFNN.getClassOutputValues()); } }