main.mFFNN.java Source code

Introduction

Here is the source code for main.mFFNN.java

Source

/*
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package main;

import FeedForwardNeuralNetwork.FeedForwardNeuralNetwork;
import java.io.BufferedReader;
import java.io.FileOutputStream;
import java.io.FileReader;
import java.io.ObjectOutputStream;
import java.util.Scanner;
import weka.classifiers.Classifier;
import weka.classifiers.Evaluation;
import weka.core.Instances;
import weka.filters.Filter;
import weka.filters.supervised.attribute.Discretize;

/**
 *
 * @author user-ari
 */
public class mFFNN {

    void saveModel(Classifier C, String namaFile) throws Exception {
        //SAVE 
        // serialize model
        weka.core.SerializationHelper.write(namaFile, C);
    }

    public static void main(String[] args) throws Exception {
        mFFNN m = new mFFNN();
        BufferedReader breader = null;
        breader = new BufferedReader(new FileReader("src\\main\\iris.arff"));
        Instances fileTrain = new Instances(breader);
        fileTrain.setClassIndex(fileTrain.numAttributes() - 1);
        System.out.println(fileTrain);
        breader.close();
        System.out.println("mFFNN!!!\n\n");
        FeedForwardNeuralNetwork FFNN = new FeedForwardNeuralNetwork();

        Evaluation eval = new Evaluation(fileTrain);
        FFNN.buildClassifier(fileTrain);

        eval.evaluateModel(FFNN, fileTrain);

        //OUTPUT
        Scanner scan = new Scanner(System.in);
        System.out.println(eval.toSummaryString("=== Stratified cross-validation ===\n" + "=== Summary ===", true));
        System.out.println(eval.toClassDetailsString("=== Detailed Accuracy By Class ==="));
        System.out.println(eval.toMatrixString("===Confusion matrix==="));
        System.out.println(eval.fMeasure(1) + " " + eval.recall(1));
        System.out.println("\nDo you want to save this model(1/0)? ");
        FFNN.distributionForInstance(fileTrain.get(0));
        /* int c = scan.nextInt();
        if (c == 1 ){
         System.out.print("Please enter your file name (*.model) : ");
         String infile = scan.next();
         m.saveModel(FFNN,infile);
        }
        else {
        System.out.print("Model not saved.");
        } */
    }
}