newsclassifier.NewsClassifier.java Source code

Introduction

Here is the source code for newsclassifier.NewsClassifier.java

Source

/*
 * 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 newsclassifier;

import weka.core.*;
import weka.classifiers.*;
import weka.classifiers.bayes.NaiveBayes;
import weka.classifiers.bayes.NaiveBayesMultinomial;
import weka.classifiers.lazy.IBk;
import weka.classifiers.trees.J48;
import weka.classifiers.functions.MultilayerPerceptron;
import weka.core.converters.ConverterUtils.DataSource;
import weka.experiment.InstanceQuery;
import weka.filters.Filter;
import weka.filters.unsupervised.attribute.ClassAssigner;
import weka.filters.unsupervised.attribute.NumericToNominal;
import weka.filters.unsupervised.attribute.StringToWordVector;

import java.io.File;
import java.util.*;
import weka.classifiers.functions.SMO;
import weka.classifiers.trees.RandomForest;
import weka.filters.unsupervised.attribute.StringToNominal;

/**
 *
 * @author USER
 */
public class NewsClassifier {

    private int mode; //1 untuk naive bayes, 2 untuk tree, 3 untuk KNN, 4 untuk ANN
    private Instances data;
    private Instances unLabeledData;
    private Classifier classifier;

    public NewsClassifier() throws Exception {
        data = null;
        mode = 1;
        classifier = null;
    }

    public void LoadDB() throws Exception {
        Class.forName("com.mysql.jdbc.Driver");
        InstanceQuery query = new InstanceQuery();
        query.setDatabaseURL("jdbc:mysql://localhost:3306/news_aggregator");
        query.setUsername("root");
        query.setPassword("");
        //query.setQuery("SELECT full_text,id_kelas FROM artikel NATURAL JOIN artikel_kategori_verified");
        query.setQuery(
                "SELECT judul,full_text,label FROM artikel NATURAL JOIN artikel_kategori_verified NATURAL JOIN kategori");
        data = query.retrieveInstances();
    }

    public void StrToWV(String sFile) throws Exception {
        StringToWordVector filter = new StringToWordVector();
        filter.setInputFormat(data);
        /*filter.setIDFTransform(false);
        filter.setTFTransform(true);
        filter.setAttributeIndices("1-2");
        //attributenameprefix
        filter.setDoNotOperateOnPerClassBasis(true);
        filter.setInvertSelection(false);
        filter.setLowerCaseTokens(true);
        filter.setMinTermFreq(1);
        //filter.setNormalizeDocLength(true);
        filter.setOutputWordCounts(false);
        //filter.setPeriodicPruning(-1);
        //filter.setStemmer(null);
        filter.setStopwords(new File(sFile));*/
        //String[] opts = weka.core.Utils.splitOptions("-tokenizer \"weka.core.tokenizers.WordTokenizer -delimiters \\\" \\\\r \\\\t.,;:\\\\\\'\\\\\\\"()?!1234567890 `~!@#\\\\\\%^&*[]-_+={}\\\\\\\\/|?><  \\\\r\\\\t\\\"\"");
        String[] opts = weka.core.Utils.splitOptions(
                "-R 1-2 -W 3000 -prune-rate -1.0 -T -N 0 -L -S -stemmer weka.core.stemmers.NullStemmer -M 1 -O -stopwords \"C:\\\\Users\\\\USER\\\\Dropbox\\\\Works\\\\IF\\\\AI\\\\Tubes 2\\\\s.txt\" -tokenizer \"weka.core.tokenizers.WordTokenizer -delimiters \\\"   \\\\t.,;:\\\\\\'\\\\\\\"()?!1234567890 `~!@#\\\\\\%^&*[]-_+={}\\\\\\\\/|?><   \\\\t\\\"\"");
        filter.setOptions(opts);
        //belum pake delimiter!!
        filter.setWordsToKeep(3000);

        data = Filter.useFilter(data, filter);
        //return newData;
        //data = newData;
    }

    public void StrtoNom() throws Exception {
        StringToNominal filter = new StringToNominal();
        //NumericToNominal filter = new NumericToNominal();
        filter.setInputFormat(data);
        //filter.setOptions("-R 1");
        String[] opts = { "-R", "first" };
        filter.setOptions(opts);
        //filter.setAttributeRange("first");
        data = Filter.useFilter(data, filter);
    }

    public void ClassAssigner() throws Exception {
        ClassAssigner filter = new ClassAssigner();
        filter.setInputFormat(data);
        //filter3.setClassIndex("last");
        filter.setClassIndex("first");
        data = Filter.useFilter(data, filter);
    }

    public void CrossValidation(Classifier cls, int n) throws Exception {
        data.setClassIndex(0);
        Evaluation eval = new Evaluation(data);
        cls.buildClassifier(data);
        eval.crossValidateModel(cls, data, n, new Random(1));
        System.out.println(eval.toSummaryString("Results", false));
        //System.out.println(eval.toClassDetailsString());
        //System.out.println(eval.toMatrixString());
    }

    public void classify() throws Exception {
        unLabeledData = DataSource.read("unlabeled.arff");
        unLabeledData.setClassIndex(unLabeledData.numAttributes() - 1);
        Instances LabeledData = new Instances(unLabeledData);

        for (int i = 0; i < unLabeledData.numInstances(); ++i) {
            double clsLabel = classifier.classifyInstance(unLabeledData.instance(i));
            LabeledData.instance(i).setClassValue(clsLabel);
        }
        //System.out.println(LabeledData.toString());
    }

    public void save(String filename) throws Exception {
        SerializationHelper.write(filename, classifier);
    }

    public void load(String filename) throws Exception {
        classifier = (Classifier) SerializationHelper.read(filename);
    }

    public static void main(String[] args) {
        try {
            NewsClassifier nc = new NewsClassifier();
            //nc.readData();
            nc.LoadDB();
            nc.StrToWV("s.txt");
            //System.out.println(nc.data.toString());
            nc.StrtoNom();
            //nc.ClassAssigner();
            //System.out.println(nc.data.toString());
            //RandomForest cls = new RandomForest();
            SMO cls = new SMO();
            //NaiveBayesMultinomial cls = new(NaiveBayesMultinomial);
            nc.CrossValidation(cls, 10);
        } catch (Exception e) {
            e.printStackTrace();
        }
    }
}