Package fr.lip6.jkernelmachines.example

Source Code of fr.lip6.jkernelmachines.example.SVMExample

/**
    This file is part of JkernelMachines.

    JkernelMachines 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 3 of the License, or
    (at your option) any later version.

    JkernelMachines 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 JkernelMachines.  If not, see <http://www.gnu.org/licenses/>.

    Copyright David Picard - 2012

*/
package fr.lip6.jkernelmachines.example;

import java.io.IOException;
import java.util.List;

import fr.lip6.jkernelmachines.classifier.LaSVM;
import fr.lip6.jkernelmachines.evaluation.ApEvaluator;
import fr.lip6.jkernelmachines.io.LibSVMImporter;
import fr.lip6.jkernelmachines.kernel.typed.DoubleGaussL2;
import fr.lip6.jkernelmachines.type.TrainingSample;

/**
* <p>This class is a very simple introduction to the use of jkernelmachines.</p>
*
* <p>It reads data from a file in libsvm format, then trains a SVM classifier using
* LaSVM algorithm with a Gaussian kernel. Finally, output values are computed on some
* samples and error rate is computed.</p>
*
* @author picard
*
*/
public class SVMExample {

  /**
   * @param args
   */
  public static void main(String[] args) {
   
    //checking arguments
    if(args.length < 1) {
      System.out.println("Usage: SVMExample trainfile testfile");
      return;
    }
   
    //parsing samples from a file using libsvm format
    List<TrainingSample<double[]>> train = null;
    List<TrainingSample<double[]>> test = null;
    try {
      train = LibSVMImporter.importFromFile(args[0]);
    }
    catch (IOException e) {
      System.out.println("Error parsing file "+args[0]);
      return;
    }
    try {
      test = LibSVMImporter.importFromFile(args[1]);
    }
    catch (IOException e) {
      System.out.println("Error parsing file "+args[1]);
      return;
    }
   
    //setting kernel
    DoubleGaussL2 kernel = new DoubleGaussL2();
    kernel.setGamma(2.0);
   
    //setting SVM parameters
    LaSVM<double[]> svm = new LaSVM<double[]>(kernel);
    svm.setC(10); //C hyperparameter
       
    //evaluation on testing set using evaluator
    ApEvaluator<double[]> ape = new ApEvaluator<double[]>();
    ape.setClassifier(svm);
    ape.setTrainingSet(train);
    ape.setTestingSet(test);
    ape.evaluate(); // training and evaluating at the same time
   
    // printing average precision obtained
    System.out.println("Average Precision: "+ape.getScore());
  }

}
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