sentinets.TrainModel.java Source code

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Here is the source code for sentinets.TrainModel.java

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/*******************************************************************************
 * Copyright (c) 2015 University of Illinois Board of Trustees, All rights reserved.
 * Developed at GSLIS/ the iSchool, by Dr. Jana Diesner, Shubhanshu Mishra, Liang Tao, and Chieh-Li Chin.    
 * This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or any later version.
 * This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
 * You should have received a copy of the GNU General Public License along with this program; if not, see <http://www.gnu.org/licenses>.
 *******************************************************************************/
package sentinets;

import java.io.File;
import java.io.FileInputStream;
import java.io.FileNotFoundException;
import java.io.FileOutputStream;
import java.io.IOException;
import java.io.ObjectInputStream;
import java.io.ObjectOutputStream;
import java.util.Random;

import weka.classifiers.Classifier;
import weka.classifiers.Evaluation;
import weka.classifiers.bayes.NaiveBayes;
import weka.classifiers.functions.SMO;
import weka.classifiers.meta.FilteredClassifier;
import weka.classifiers.trees.J48;
import weka.core.Instances;
import weka.core.converters.CSVLoader;
import weka.filters.unsupervised.attribute.Remove;

public class TrainModel {
    Instances ins;
    String inputFile, outputFile;
    FilteredClassifier cls;

    public TrainModel(String inputFile, String outputFile) {
        this.inputFile = inputFile;
        this.outputFile = outputFile;
        this.setInstances(this.inputFile);
    }

    public void setInstances(String inputFile) {
        String[] nominalVals = { "42:positive,negative,neutral" };
        ins = null;
        try {
            CSVLoader csvSource = new CSVLoader();
            csvSource.setSource(new File(inputFile));
            csvSource.setFieldSeparator("\t");
            csvSource.setNominalAttributes("15-16");
            csvSource.setStringAttributes("3,4,6,8,10-12,14");
            csvSource.setNominalLabelSpecs(nominalVals);
            ins = csvSource.getDataSet();
            Remove r = new Remove();
            r.setAttributeIndices("3-4,6,8,10-12,14,40-41");
            r.setInputFormat(ins);
            ins = Remove.useFilter(ins, r);
            //System.out.println(unlabled.toSummaryString());
            r = new Remove();
            System.out.println(ins.toSummaryString());

        } catch (FileNotFoundException e) {
            e.printStackTrace();
        } catch (IOException e) {
            e.printStackTrace();
        } catch (Exception e) {
            e.printStackTrace();
        }
        int cIdx = ins.numAttributes() - 1;
        ins.setClassIndex(cIdx);
    }

    public void runExps() {
        Classifier c1 = new SMO();
        Classifier c2 = new J48();
        Classifier c3 = new NaiveBayes();
        trainModel(c1, "SVM");
        trainModel(c2, "J48");
        trainModel(c3, "Naive Bayes");

    }

    public void trainModel(Classifier c, String name) {
        Evaluation e;
        try {
            e = new Evaluation(ins);
            e.crossValidateModel(c, ins, 10, new Random(1));
            System.out.println("****Results of " + name + "****");
            System.out.println(e.toSummaryString());
            System.out.println(e.toClassDetailsString());
            System.out.println(e.toCumulativeMarginDistributionString());
            System.out.println(e.toMatrixString());
            System.out.println("*********************");
            TrainModel.saveModel(c, name);
        } catch (Exception e1) {
            e1.printStackTrace();
        }

    }

    private static void saveModel(Classifier c, String name) throws IOException {

        ObjectOutputStream oos = null;
        try {
            oos = new ObjectOutputStream(new FileOutputStream("./models/" + name + ".model"));

        } catch (FileNotFoundException e1) {
            e1.printStackTrace();
        } catch (IOException e1) {
            e1.printStackTrace();
        }
        oos.writeObject(c);
        oos.flush();
        oos.close();

    }

    private static Classifier loadModel(String name) throws Exception {

        Classifier classifier;

        FileInputStream fis = new FileInputStream("./models/" + name + ".model");
        ObjectInputStream ois = new ObjectInputStream(fis);

        classifier = (Classifier) ois.readObject();
        ois.close();

        return classifier;
    }

    public static void main(String[] args) {
        String dataFile = "TEST_POS.tsv";
        System.out.println("args.length=" + args.length);
        for (int i = 0; i < args.length; i++) {
            System.out.printf("args[%s]=%s\n", i, args[i]);
        }
        if (args.length == 1) {
            dataFile = args[0];
        } else if (args.length > 1) {
            System.out.println("Format for calling is:\n");
            System.out.println("ant TrainModel <filepath>");
            System.exit(-1);
        }
        TrainModel t = new TrainModel(dataFile, "");
        t.runExps();
    }
}