Examples of org.data2semantics.exp.old.utils.Experimenter

Package org.data2semantics.exp.old.utils

Examples of org.data2semantics.exp.old.utils.Experimenter

org.data2semantics.exp.old.utils.Experimenter

    ResultsTable resultsSTF = new ResultsTable();
    ResultsTable resultsSTP = new ResultsTable();
    ResultsTable resultsIGW = new ResultsTable();
    ResultsTable resultsIGP = new ResultsTable();


    Experimenter experimenter = new Experimenter(NUMBER_OF_PROC);
    Thread expT = new Thread(experimenter);
    expT.setDaemon(true);
    expT.start();






    try {
      for (GeneralPredictionDataSetParameters params : dataSetsParams) {
        dataset = DataSetFactory.createPropertyPredictionDataSet(params);
        //dataset.removeSmallClasses(5);
        dataset.setLabels(labels);
        //dataset.removeVertexAndEdgeLabels();


        
        
        resultsWL.newRow(dataset.getLabel() + " WLSubTreeKernel");
        for (int i = 0; i < 4; i++) {
          if (experimenter.hasSpace()) {    
            int fileId = (int) (Math.random() * 100000000);  
            File file = new File(DATA_DIR + fileId + "_" + "WL" + "_" + i + ".txt");
            exp = new PropertyPredictionExperiment(new PropertyPredictionDataSet(dataset), new WLSubTreeKernel(i), seeds, cs, maxClassSize, new FileOutputStream(file));
            experimenter.addExperiment(exp);
            resultsWL.addResult(exp.getResults().getAccuracy());
            resultsWL.addResult(exp.getResults().getF1());
          }
        }




        
        resultsSTF.newRow(dataset.getLabel() + " IntersectionFullSubTree");
        for (int i = 0; i < 4; i++) {


          if (experimenter.hasSpace()) {    
            int fileId = (int) (Math.random() * 100000000);  
            File file = new File(DATA_DIR + fileId + "_" + "IntersectionFullSubTree" + "_" + i + ".txt");
            exp = new PropertyPredictionExperiment(new PropertyPredictionDataSet(dataset), new IntersectionSubTreeKernel(i, 1), seeds, cs, maxClassSize, new FileOutputStream(file));
            experimenter.addExperiment(exp);
            resultsSTF.addResult(exp.getResults().getAccuracy());
            resultsSTF.addResult(exp.getResults().getF1());
          }
        }


        resultsSTP.newRow(dataset.getLabel() + " IntersectionPartialSubTree");
        for (int i = 0; i < 4; i++) {
          if (experimenter.hasSpace()) {    
            int fileId = (int) (Math.random() * 100000000);  
            File file = new File(DATA_DIR + fileId + "_" + "IntersectionPartialSubTree" + "_" + i + ".txt");
            exp = new PropertyPredictionExperiment(new PropertyPredictionDataSet(dataset), new IntersectionPartialSubTreeKernel(i, 0.01), seeds, cs, maxClassSize, new FileOutputStream(file));
            experimenter.addExperiment(exp);
            resultsSTP.addResult(exp.getResults().getAccuracy());
            resultsSTP.addResult(exp.getResults().getF1());
          }
        }


        //*/




        
        resultsIGP.newRow(dataset.getLabel() + " IntersectionGraphPath");
        for (int i = 1; i < 3; i++) {
          if (experimenter.hasSpace()) {    
            int fileId = (int) (Math.random() * 100000000);  
            File file = new File(DATA_DIR + fileId + "_" + "IntersectionGraphPath" + "_" + i + ".txt");
            exp = new PropertyPredictionExperiment(new PropertyPredictionDataSet(dataset), new IntersectionGraphPathKernel(i, 1), seeds, cs, maxClassSize, new FileOutputStream(file));
            experimenter.addExperiment(exp);
            resultsIGP.addResult(exp.getResults().getAccuracy());
            resultsIGP.addResult(exp.getResults().getF1());
          }
        }        


        resultsIGW.newRow(dataset.getLabel() + " IntersectionGraphWalk");
        for (int i = 1; i < 3; i++) {
          if (experimenter.hasSpace()) {    
            int fileId = (int) (Math.random() * 100000000);  
            File file = new File(DATA_DIR + fileId + "_" + "IntersectionGraphWalk" + "_" + i + ".txt");
            exp = new PropertyPredictionExperiment(new PropertyPredictionDataSet(dataset), new IntersectionGraphWalkKernel(i, 1), seeds, cs, maxClassSize, new FileOutputStream(file));
            experimenter.addExperiment(exp);
            resultsIGW.addResult(exp.getResults().getAccuracy());
            resultsIGW.addResult(exp.getResults().getF1());
          }
        }
        //*/        


      }
    } catch (Exception e) {
      e.printStackTrace();
    }


    experimenter.stop();


    while (expT.isAlive()) {
      try {
        Thread.sleep(1000);
      } catch (Exception e) {

View Full Code Here


    boolean inference = false;
    for (int i = 1; i <= depth; i++) {
      resTable.newRow("WL RDF, no inference, depth="+i);
      for (int it : iterations) {
        Experimenter experimenter = new Experimenter(2);
        Thread expT = new Thread(experimenter);
        expT.setDaemon(true);
        expT.start();        


        List<List<Result>> res = new ArrayList<List<Result>>();
        for (long seed : seeds) {
          long[] s2 = new long[1];
          s2[0] = seed;
          createGeoDataSet(seed, fraction, minSize, "http://data.bgs.ac.uk/ref/Lexicon/hasTheme");
          KernelExperiment<RDFGraphKernel> exp = new RDFOldKernelExperiment(new ECML2013RDFWLSubTreeKernel(it, i, inference, true, false), s2, parms, dataset, instances, labels, blackList);
          res.add(exp.getResults());


          System.out.println("Running WL RDF: " + i + " " + it);
          if (experimenter.hasSpace()) {
            experimenter.addExperiment(exp);
          }




        }


        experimenter.stop();
        try {
          while (expT.isAlive()) {
            Thread.sleep(1000);
          }
        } catch (Exception e) {
          e.printStackTrace();
        }


        for (Result res2 : Result.mergeResultLists(res)) {
          resTable.addResult(res2);
        }
      }
    }
    saveResults(resTable, "geo_theme.ser");




    inference = true;
    for (int i = 1; i <= depth; i++) {
      resTable.newRow("WL RDF, inference, depth="+i);
      for (int it : iterations) {
        Experimenter experimenter = new Experimenter(2);
        Thread expT = new Thread(experimenter);
        expT.setDaemon(true);
        expT.start();




        List<List<Result>> res = new ArrayList<List<Result>>();
        for (long seed : seeds) {
          long[] s2 = new long[1];
          s2[0] = seed;
          createGeoDataSet(seed, fraction, minSize, "http://data.bgs.ac.uk/ref/Lexicon/hasTheme");
          KernelExperiment<RDFGraphKernel> exp = new RDFOldKernelExperiment(new ECML2013RDFWLSubTreeKernel(it, i, inference, true, false), s2, parms, dataset, instances, labels, blackList);
          res.add(exp.getResults());


          System.out.println("Running WL RDF: " + i + " " + it);
          if (experimenter.hasSpace()) {
            experimenter.addExperiment(exp);
          }




        }


        experimenter.stop();


        while (expT.isAlive()) {
          try {
            Thread.sleep(1000);
          } catch (Exception e) {
            e.printStackTrace();
          }
        }


        for (Result res2 : Result.mergeResultLists(res)) {
          resTable.addResult(res2);
        }
      }
    }
    saveResults(resTable, "geo_theme.ser");




    inference = false;
    for (int i = 1; i <= depth; i++) {
      resTable.newRow("IST, no inference, depth="+i);


      Experimenter experimenter = new Experimenter(2);
      Thread expT = new Thread(experimenter);
      expT.setDaemon(true);
      expT.start();


      List<List<Result>> res = new ArrayList<List<Result>>();
      for (long seed : seeds) {
        long[] s2 = new long[1];
        s2[0] = seed;
        createGeoDataSet(seed, fraction,  minSize, "http://data.bgs.ac.uk/ref/Lexicon/hasTheme");
        KernelExperiment<RDFGraphKernel> exp = new RDFOldKernelExperiment(new RDFIntersectionSubTreeKernel(i, 1, inference, true, false), s2, parms, dataset, instances, labels, blackList);
        res.add(exp.getResults());


        System.out.println("Running IST: " + i);
        if (experimenter.hasSpace()) {
          experimenter.addExperiment(exp);
        }
      }


      experimenter.stop();


      while (expT.isAlive()) {
        try {
          Thread.sleep(1000);
        } catch (Exception e) {
          e.printStackTrace();
        }
      }


      for (Result res2 : Result.mergeResultLists(res)) {
        resTable.addResult(res2);
      }
    }
    saveResults(resTable, "geo_theme.ser");




    inference = true;
    for (int i = 1; i <= depth; i++) {
      resTable.newRow("IST, inference, depth="+i);


      Experimenter experimenter = new Experimenter(2);
      Thread expT = new Thread(experimenter);
      expT.setDaemon(true);
      expT.start();


      List<List<Result>> res = new ArrayList<List<Result>>();
      for (long seed : seeds) {
        long[] s2 = new long[1];
        s2[0] = seed;
        createGeoDataSet(seed, fraction,  minSize, "http://data.bgs.ac.uk/ref/Lexicon/hasTheme");
        KernelExperiment<RDFGraphKernel> exp = new RDFOldKernelExperiment(new RDFIntersectionSubTreeKernel(i, 1, inference, true, false), s2, parms, dataset, instances, labels, blackList);
        res.add(exp.getResults());




        System.out.println("Running IST: " + i);
        if (experimenter.hasSpace()) {
          experimenter.addExperiment(exp);
        }


      }


      experimenter.stop();


      while (expT.isAlive()) {
        try {
          Thread.sleep(1000);
        } catch (Exception e) {
          e.printStackTrace();
        }
      }


      for (Result res2 : Result.mergeResultLists(res)) {
        resTable.addResult(res2);
      }
    }
    saveResults(resTable, "geo_theme.ser");




    inference = false;
    for (int i = 1; i <= depth; i++) {
      resTable.newRow("IPST, no inference, depth="+i);


      Experimenter experimenter = new Experimenter(2);
      Thread expT = new Thread(experimenter);
      expT.setDaemon(true);
      expT.start();


      List<List<Result>> res = new ArrayList<List<Result>>();
      for (long seed : seeds) {
        long[] s2 = new long[1];
        s2[0] = seed;
        createGeoDataSet(seed, fraction,  minSize, "http://data.bgs.ac.uk/ref/Lexicon/hasTheme");
        KernelExperiment<RDFGraphKernel> exp = new RDFOldKernelExperiment(new RDFIntersectionPartialSubTreeKernel(i, 0.01, inference, true, false), s2, parms, dataset, instances, labels, blackList);
        res.add(exp.getResults());


        System.out.println("Running IPST: " + i);
        if (experimenter.hasSpace()) {
          experimenter.addExperiment(exp);
        }
      }


      experimenter.stop();


      while (expT.isAlive()) {
        try {
          Thread.sleep(1000);
        } catch (Exception e) {
          e.printStackTrace();
        }
      }


      for (Result res2 : Result.mergeResultLists(res)) {
        resTable.addResult(res2);
      }
    }
    saveResults(resTable, "geo_theme.ser");






    inference = true;
    for (int i = 1; i <= depth; i++) {
      resTable.newRow("IPST, inference, depth="+i);


      Experimenter experimenter = new Experimenter(2);
      Thread expT = new Thread(experimenter);
      expT.setDaemon(true);
      expT.start();


      List<List<Result>> res = new ArrayList<List<Result>>();
      for (long seed : seeds) {
        long[] s2 = new long[1];
        s2[0] = seed;
        createGeoDataSet(seed, fraction,  minSize, "http://data.bgs.ac.uk/ref/Lexicon/hasTheme");
        KernelExperiment<RDFGraphKernel> exp = new RDFOldKernelExperiment(new RDFIntersectionPartialSubTreeKernel(i, 0.01, inference, true, false), s2, parms, dataset, instances, labels, blackList);
        res.add(exp.getResults());


        System.out.println("Running IPST: " + i);
        if (experimenter.hasSpace()) {
          experimenter.addExperiment(exp);
        }
      }


      experimenter.stop();


      while (expT.isAlive()) {
        try {
          Thread.sleep(1000);
        } catch (Exception e) {

View Full Code Here

    ResultsTable resultsSTF = new ResultsTable();
    ResultsTable resultsSTP = new ResultsTable();
    ResultsTable resultsIGW = new ResultsTable();
    ResultsTable resultsIGP = new ResultsTable();


    Experimenter experimenter = new Experimenter(NUMBER_OF_PROC);
    Thread expT = new Thread(experimenter);
    expT.setDaemon(true);
    expT.start();






    try {
      for (BinaryPropertyPredictionDataSetParameters params : dataSetsParams) {
        dataset = DataSetFactory.createPropertyPredictionDataSet(params);
        dataset.removeSmallClasses(5);
        dataset.setLabels(labels);
        //dataset.removeVertexAndEdgeLabels();


        resultsWL.newRow(dataset.getLabel() + " WLSubTreeKernel");


        for (int i = 0; i < 4; i++) {
          if (experimenter.hasSpace()) {    
            int fileId = (int) (Math.random() * 100000000);  
            File file = new File(DATA_DIR + fileId + "_" + "WL" + "_" + i + ".txt");
            exp = new PropertyPredictionExperiment(new PropertyPredictionDataSet(dataset), new WLSubTreeKernel(i), seeds, cs, maxClassSize, new FileOutputStream(file));
            experimenter.addExperiment(exp);
            resultsWL.addResult(exp.getResults().getAccuracy());
            resultsWL.addResult(exp.getResults().getF1());
            
            System.out.println("Running WL, it " + i + " on " + dataset.getLabel());
          }
        }


        
        resultsSTF.newRow(dataset.getLabel() + " IntersectionFullSubTree");
        for (int i = 0; i < 3; i++) {


          if (experimenter.hasSpace()) {    
            int fileId = (int) (Math.random() * 100000000);  
            File file = new File(DATA_DIR + fileId + "_" + "IntersectionFullSubTree" + "_" + i + ".txt");
            exp = new PropertyPredictionExperiment(new PropertyPredictionDataSet(dataset), new IntersectionSubTreeKernel(i, 1), seeds, cs, maxClassSize, new FileOutputStream(file));
            experimenter.addExperiment(exp);
            resultsSTF.addResult(exp.getResults().getAccuracy());
            resultsSTF.addResult(exp.getResults().getF1());
            
            System.out.println("Running STF, it " + i + " on " + dataset.getLabel());
          }
        }


        resultsSTP.newRow(dataset.getLabel() + " IntersectionPartialSubTree");
        for (int i = 0; i < 3; i++) {
          if (experimenter.hasSpace()) {    
            int fileId = (int) (Math.random() * 100000000);  
            File file = new File(DATA_DIR + fileId + "_" + "IntersectionPartialSubTree" + "_" + i + ".txt");
            exp = new PropertyPredictionExperiment(new PropertyPredictionDataSet(dataset), new IntersectionPartialSubTreeKernel(i, 0.01), seeds, cs, maxClassSize, new FileOutputStream(file));
            experimenter.addExperiment(exp);
            resultsSTP.addResult(exp.getResults().getAccuracy());
            resultsSTP.addResult(exp.getResults().getF1());
            
            System.out.println("Running STP, it " + i + " on " + dataset.getLabel());
          }
        }




        
        resultsIGP.newRow(dataset.getLabel() + " IntersectionGraphPath");
        for (int i = 1; i < 3; i++) {
          if (experimenter.hasSpace()) {    
            int fileId = (int) (Math.random() * 100000000);  
            File file = new File(DATA_DIR + fileId + "_" + "IntersectionGraphPath" + "_" + i + ".txt");
            exp = new PropertyPredictionExperiment(new PropertyPredictionDataSet(dataset), new IntersectionGraphPathKernel(i, 1), seeds, cs, maxClassSize, new FileOutputStream(file));
            experimenter.addExperiment(exp);
            resultsIGP.addResult(exp.getResults().getAccuracy());
            resultsIGP.addResult(exp.getResults().getF1());
            
            System.out.println("Running IGP, it " + i + " on " + dataset.getLabel());
          }
        }        


        resultsIGW.newRow(dataset.getLabel() + " IntersectionGraphWalk");
        for (int i = 1; i < 3; i++) {
          if (experimenter.hasSpace()) {    
            int fileId = (int) (Math.random() * 100000000);  
            File file = new File(DATA_DIR + fileId + "_" + "IntersectionGraphWalk" + "_" + i + ".txt");
            exp = new PropertyPredictionExperiment(new PropertyPredictionDataSet(dataset), new IntersectionGraphWalkKernel(i, 1), seeds, cs, maxClassSize, new FileOutputStream(file));
            experimenter.addExperiment(exp);
            resultsIGW.addResult(exp.getResults().getAccuracy());
            resultsIGW.addResult(exp.getResults().getF1());
            
            System.out.println("Running IGW, it " + i + " on " + dataset.getLabel());
          }
        }
        //*/




      }
    } catch (Exception e) {
      e.printStackTrace();
    }


    experimenter.stop();


    while (expT.isAlive()) {
      try {
        Thread.sleep(1000);
      } catch (Exception e) {

View Full Code Here

    ResultsTable resultsSTF = new ResultsTable();
    ResultsTable resultsSTP = new ResultsTable();
    ResultsTable resultsIGW = new ResultsTable();
    ResultsTable resultsIGP = new ResultsTable();


    Experimenter experimenter = new Experimenter(NUMBER_OF_PROC);
    Thread expT = new Thread(experimenter);
    expT.setDaemon(true);
    expT.start();






    try {
      for (LinkPredictionDataSetParameters params : dataSetsParams) {
        dataset = DataSetFactory.createLinkPredictonDataSet(params);
        //dataset.removeSmallClasses(5);


        resultsWL.newRow(dataset.getLabel() + " WLSubTreeKernel");
        for (int i = 0; i < 3; i++) {
          if (experimenter.hasSpace()) {    
            int fileId = (int) (Math.random() * 100000000);  
            File file = new File(DATA_DIR + "_" + "WL" + fileId + "_" + i + ".txt");
            exp = new LinkPredictionExperiment(new LinkPredictionDataSet(dataset), new WLSubTreeKernel(i), new WLSubTreeKernel(i), 3.0/6.0, 3.0/6.0, seeds, cs, maxClassSize, new FileOutputStream(file));
            experimenter.addExperiment(exp);
            resultsWL.addResult(exp.getResults().getAccuracy());
            resultsWL.addResult(exp.getResults().getF1());
            resultsWL.addResult(exp.getResults().getrPrecision());
            resultsWL.addResult(exp.getResults().getAveragePrecision());
            resultsWL.addResult(exp.getResults().getNdcg());
            
            System.out.println("Running WL, it " + i + " on " + dataset.getLabel());
          }
        }




        resultsSTF.newRow(dataset.getLabel() + " IntersectionFullSubTreeKernel");
        for (int i = 0; i < 3; i++) {


          if (experimenter.hasSpace()) {    
            int fileId = (int) (Math.random() * 100000000);  
            File file = new File(DATA_DIR + "_" + "IntersectionFullSubTree" + fileId + "_" + i + ".txt");
            exp = new LinkPredictionExperiment(new LinkPredictionDataSet(dataset), new IntersectionSubTreeKernel(i,1), new IntersectionSubTreeKernel(i,1), 3.0/6.0, 3.0/6.0, seeds, cs, maxClassSize, new FileOutputStream(file));
            experimenter.addExperiment(exp);
            resultsSTF.addResult(exp.getResults().getAccuracy());
            resultsSTF.addResult(exp.getResults().getF1());
            resultsSTF.addResult(exp.getResults().getrPrecision());
            resultsSTF.addResult(exp.getResults().getAveragePrecision());
            resultsSTF.addResult(exp.getResults().getNdcg());
            
            System.out.println("Running STF, it " + i + " on " + dataset.getLabel());
          }
        }


        resultsSTP.newRow(dataset.getLabel() + " IntersectionPartialSubTreeKernel");
        for (int i = 0; i < 3; i++) {
          if (experimenter.hasSpace()) {    
            int fileId = (int) (Math.random() * 100000000);  
            File file = new File(DATA_DIR + "_" + "IntersectionPartialSubTree" + fileId + "_" + i + ".txt");
            exp = new LinkPredictionExperiment(new LinkPredictionDataSet(dataset), new IntersectionPartialSubTreeKernel(i,0.01), new IntersectionPartialSubTreeKernel(i,0.01), 3.0/6.0, 3.0/6.0, seeds, cs, maxClassSize, new FileOutputStream(file));  
            experimenter.addExperiment(exp);
            resultsSTP.addResult(exp.getResults().getAccuracy());
            resultsSTP.addResult(exp.getResults().getF1());
            resultsSTP.addResult(exp.getResults().getrPrecision());
            resultsSTP.addResult(exp.getResults().getAveragePrecision());
            resultsSTP.addResult(exp.getResults().getNdcg());
            
            System.out.println("Running STP, it " + i + " on " + dataset.getLabel());
          }
        }




        /*
        resultsIGW.newRow(dataset.getLabel() + " IntersectionGraphWalkKernel");
        for (int i = 1; i < 3; i++) {
          if (experimenter.hasSpace()) {    
            int fileId = (int) (Math.random() * 100000000);  
            File file = new File(DATA_DIR + "_" + "IntersectionGraphWalk" + fileId + "_" + i + ".txt");
            exp = new LinkPredictionExperiment(new LinkPredictionDataSet(dataset), new IntersectionGraphWalkKernel(i,1), new IntersectionGraphWalkKernel(i,1), 0.5, 0.5, seeds, cs, maxClassSize, new FileOutputStream(file));  
            experimenter.addExperiment(exp);
            resultsIGW.addResult(exp.getResults().getAccuracy());
            resultsIGW.addResult(exp.getResults().getF1());
            resultsIGW.addResult(exp.getResults().getrPrecision());
            resultsIGW.addResult(exp.getResults().getAveragePrecision());
            resultsIGW.addResult(exp.getResults().getNdcg());
            
            System.out.println("Running IGW, it " + i + " on " + dataset.getLabel());
          }
        }        


        resultsIGP.newRow(dataset.getLabel() + " IntersectionGraphPathKernel");
        for (int i = 1; i < 3; i++) {
          if (experimenter.hasSpace()) {    
            int fileId = (int) (Math.random() * 100000000);  
            File file = new File(DATA_DIR + "_" + "IntersectionGraphPath" + fileId + "_" + i + ".txt");
            exp = new LinkPredictionExperiment(new LinkPredictionDataSet(dataset), new IntersectionGraphPathKernel(i,1), new IntersectionGraphPathKernel(i,1), 0.5, 0.5, seeds, cs, maxClassSize, new FileOutputStream(file));  
            experimenter.addExperiment(exp);
            resultsIGP.addResult(exp.getResults().getAccuracy());
            resultsIGP.addResult(exp.getResults().getF1());
            resultsIGP.addResult(exp.getResults().getrPrecision());
            resultsIGP.addResult(exp.getResults().getAveragePrecision());
            resultsIGP.addResult(exp.getResults().getNdcg());
            
            System.out.println("Running IGP, it " + i + " on " + dataset.getLabel());
          }
        }


        //*/


      }
    } catch (Exception e) {
      e.printStackTrace();
    }


    experimenter.stop();


    while (expT.isAlive()) {
      try {
        Thread.sleep(1000);
      } catch (Exception e) {

View Full Code Here

    double[] cs = {0.001, 0.01, 0.1, 1, 10, 100, 1000};  


    PropertyPredictionDataSet dataset;
    PropertyPredictionExperiment exp;
    
    Experimenter experimenter = new Experimenter(NUMBER_OF_PROC);
    Thread expT = new Thread(experimenter);
    expT.setDaemon(true);
    expT.start();


    ResultsTable resultsWL = new ResultsTable();
    ResultsTable resultsSTF = new ResultsTable();
    ResultsTable resultsSTP = new ResultsTable();
    ResultsTable resultsIGW = new ResultsTable();
    ResultsTable resultsIGP = new ResultsTable();


    ResultsTable resultsWLadd = new ResultsTable();
    ResultsTable resultsSTFadd = new ResultsTable();
    ResultsTable resultsSTPadd = new ResultsTable();
    ResultsTable resultsIGWadd = new ResultsTable();
    ResultsTable resultsIGPadd = new ResultsTable();


    
    /**  
     * FIRST EXPERIMENT, STANDARD SETTINGS
     * 
     */    
    List<PropertyPredictionDataSetParameters> dataSetsParams = new ArrayList<PropertyPredictionDataSetParameters>();


    
    dataSetsParams.add(new PropertyPredictionDataSetParameters(testSetA, "http://swrc.ontoware.org/ontology#affiliation", "http://swrc.ontoware.org/ontology#employs", 1, false, false));
    dataSetsParams.add(new PropertyPredictionDataSetParameters(testSetA, "http://swrc.ontoware.org/ontology#affiliation", "http://swrc.ontoware.org/ontology#employs", 2, false, false));
    dataSetsParams.add(new PropertyPredictionDataSetParameters(testSetA, "http://swrc.ontoware.org/ontology#affiliation", "http://swrc.ontoware.org/ontology#employs", 1, false, true));
    dataSetsParams.add(new PropertyPredictionDataSetParameters(testSetA, "http://swrc.ontoware.org/ontology#affiliation", "http://swrc.ontoware.org/ontology#employs", 2, false, true));
    
    dataSetsParams.add(new PropertyPredictionDataSetParameters(testSetA, "http://swrc.ontoware.org/ontology#affiliation", "http://swrc.ontoware.org/ontology#employs", 1, true, false));
    dataSetsParams.add(new PropertyPredictionDataSetParameters(testSetA, "http://swrc.ontoware.org/ontology#affiliation", "http://swrc.ontoware.org/ontology#employs", 2, true, false));
    dataSetsParams.add(new PropertyPredictionDataSetParameters(testSetA, "http://swrc.ontoware.org/ontology#affiliation", "http://swrc.ontoware.org/ontology#employs", 1, true, true));
    dataSetsParams.add(new PropertyPredictionDataSetParameters(testSetA, "http://swrc.ontoware.org/ontology#affiliation", "http://swrc.ontoware.org/ontology#employs", 2, true, true));
    
    /*
    dataSetsParams.add(new PropertyPredictionDataSetParameters(testSetB, "http://swrc.ontoware.org/ontology#affiliation", "http://swrc.ontoware.org/ontology#employs", 1, false, false));
    dataSetsParams.add(new PropertyPredictionDataSetParameters(testSetB, "http://swrc.ontoware.org/ontology#affiliation", "http://swrc.ontoware.org/ontology#employs", 2, false, false));
    dataSetsParams.add(new PropertyPredictionDataSetParameters(testSetB, "http://swrc.ontoware.org/ontology#affiliation", "http://swrc.ontoware.org/ontology#employs", 1, false, true));
    dataSetsParams.add(new PropertyPredictionDataSetParameters(testSetB, "http://swrc.ontoware.org/ontology#affiliation", "http://swrc.ontoware.org/ontology#employs", 2, false, true));
    
    dataSetsParams.add(new PropertyPredictionDataSetParameters(testSetB, "http://swrc.ontoware.org/ontology#affiliation", "http://swrc.ontoware.org/ontology#employs", 1, true, false));
    dataSetsParams.add(new PropertyPredictionDataSetParameters(testSetB, "http://swrc.ontoware.org/ontology#affiliation", "http://swrc.ontoware.org/ontology#employs", 2, true, false));
    dataSetsParams.add(new PropertyPredictionDataSetParameters(testSetB, "http://swrc.ontoware.org/ontology#affiliation", "http://swrc.ontoware.org/ontology#employs", 1, true, true));
    dataSetsParams.add(new PropertyPredictionDataSetParameters(testSetB, "http://swrc.ontoware.org/ontology#affiliation", "http://swrc.ontoware.org/ontology#employs", 2, true, true));
    //*/    
  


    try {
      
      
  
  
      for (PropertyPredictionDataSetParameters params : dataSetsParams) {
        dataset = DataSetFactory.createPropertyPredictionDataSet(params);
        dataset.removeSmallClasses(5);
        dataset.removeVertexAndEdgeLabels();


        resultsWL.newRow(dataset.getLabel() + " WLSubTreeKernel");
        for (int i = 0; i < 3; i++) {
          if (experimenter.hasSpace()) {  
            int fileId = (int) (Math.random() * 100000000);  
            File file = new File(DATA_DIR + fileId + "_" + "WL" + "_" + i + ".txt");
            WLSubTreeKernel kernel = new WLSubTreeKernel(i, true);
            exp = new PropertyPredictionExperiment(new PropertyPredictionDataSet(dataset), kernel, seeds, cs, new FileOutputStream(file));
            experimenter.addExperiment(exp);
            resultsWL.addResult(exp.getResults().getAccuracy());
            resultsWL.addResult(exp.getResults().getF1());
            
            System.out.println("Running WL, it " + i + " on " + dataset.getLabel());
          }
        }


        
        resultsSTF.newRow(dataset.getLabel() + " IntersectionFullSubTree");
        for (int i = 0; i < 3; i++) {


          if (experimenter.hasSpace()) {    
            int fileId = (int) (Math.random() * 100000000);  
            File file = new File(DATA_DIR + fileId + "_" + "IntersectionFullSubTree" + "_" + i + ".txt");
            exp = new PropertyPredictionExperiment(new PropertyPredictionDataSet(dataset), new IntersectionSubTreeKernel(i, 1), seeds, cs, new FileOutputStream(file));
            experimenter.addExperiment(exp);
            resultsSTF.addResult(exp.getResults().getAccuracy());
            resultsSTF.addResult(exp.getResults().getF1());
            
            System.out.println("Running STF, it " + i + " on " + dataset.getLabel());
          }


        }


        resultsSTP.newRow(dataset.getLabel() + " IntersectionPartialSubTree");
        for (int i = 0; i < 3; i++) {
          if (experimenter.hasSpace()) {    
            int fileId = (int) (Math.random() * 100000000);  
            File file = new File(DATA_DIR + fileId + "_" + "IntersectionPartialSubTree" + "_" + i + ".txt");
            exp = new PropertyPredictionExperiment(new PropertyPredictionDataSet(dataset), new IntersectionPartialSubTreeKernel(i, 0.01), seeds, cs, new FileOutputStream(file));
            experimenter.addExperiment(exp);
            resultsSTP.addResult(exp.getResults().getAccuracy());
            resultsSTP.addResult(exp.getResults().getF1());
            
            System.out.println("Running STP, it " + i + " on " + dataset.getLabel());
          }
        }




        
        resultsIGP.newRow(dataset.getLabel() + " IntersectionGraphPath");
        for (int i = 1; i < 3; i++) {
          if (experimenter.hasSpace()) {    
            int fileId = (int) (Math.random() * 100000000);  
            File file = new File(DATA_DIR + fileId + "_" + "IntersectionGraphPath" + "_" + i + ".txt");
            exp = new PropertyPredictionExperiment(new PropertyPredictionDataSet(dataset), new IntersectionGraphPathKernel(i, 1), seeds, cs, new FileOutputStream(file));
            experimenter.addExperiment(exp);
            resultsIGP.addResult(exp.getResults().getAccuracy());
            resultsIGP.addResult(exp.getResults().getF1());
            
            System.out.println("Running IGP, it " + i + " on " + dataset.getLabel());
          }
        }        


        resultsIGW.newRow(dataset.getLabel() + " IntersectionGraphWalk");
        for (int i = 1; i < 3; i++) {
          if (experimenter.hasSpace()) {    
            int fileId = (int) (Math.random() * 100000000);  
            File file = new File(DATA_DIR + fileId + "_" + "IntersectionGraphWalk" + "_" + i + ".txt");
            exp = new PropertyPredictionExperiment(new PropertyPredictionDataSet(dataset), new IntersectionGraphWalkKernel(i, 1), seeds, cs, new FileOutputStream(file));
            experimenter.addExperiment(exp);
            resultsIGW.addResult(exp.getResults().getAccuracy());
            resultsIGW.addResult(exp.getResults().getF1());
            
            System.out.println("Running IGW, it " + i + " on " + dataset.getLabel());
          }
        }
        
      }
      
      //*/
      


      /******
       * ADDITIONAL EXPERIMENTS
       */
      dataSetsParams = new ArrayList<PropertyPredictionDataSetParameters>();
      
      
      
      dataSetsParams.add(new PropertyPredictionDataSetParameters(testSetA, "http://swrc.ontoware.org/ontology#affiliation", "http://swrc.ontoware.org/ontology#employs", 1, false, false));
      dataSetsParams.add(new PropertyPredictionDataSetParameters(testSetA, "http://swrc.ontoware.org/ontology#affiliation", "http://swrc.ontoware.org/ontology#employs", 2, false, false));
      dataSetsParams.add(new PropertyPredictionDataSetParameters(testSetA, "http://swrc.ontoware.org/ontology#affiliation", "http://swrc.ontoware.org/ontology#employs", 3, false, false));
      //dataSetsParams.add(new PropertyPredictionDataSetParameters(testSetA, "http://swrc.ontoware.org/ontology#affiliation", "http://swrc.ontoware.org/ontology#employs", 4, false, false));


      
      dataSetsParams.add(new PropertyPredictionDataSetParameters(testSetA, "http://swrc.ontoware.org/ontology#affiliation", "http://swrc.ontoware.org/ontology#employs", 1, false, true));
      dataSetsParams.add(new PropertyPredictionDataSetParameters(testSetA, "http://swrc.ontoware.org/ontology#affiliation", "http://swrc.ontoware.org/ontology#employs", 2, false, true));
      dataSetsParams.add(new PropertyPredictionDataSetParameters(testSetA, "http://swrc.ontoware.org/ontology#affiliation", "http://swrc.ontoware.org/ontology#employs", 3, false, true));
      


      
      for (PropertyPredictionDataSetParameters params : dataSetsParams) {
        dataset = DataSetFactory.createPropertyPredictionDataSet(params);
        dataset.removeSmallClasses(5);
        dataset.removeVertexAndEdgeLabels();


        resultsWLadd.newRow(dataset.getLabel() + " WLSubTreeKernel");
        for (int i = 0; i < 4; i++) {
          if (experimenter.hasSpace()) {  
            int fileId = (int) (Math.random() * 100000000);  
            File file = new File(DATA_DIR + fileId + "_" + "WL" + "_" + i + ".txt");
            WLSubTreeKernel kernel = new WLSubTreeKernel(i, true);
            exp = new PropertyPredictionExperiment(new PropertyPredictionDataSet(dataset), kernel, seeds, cs, new FileOutputStream(file));
            experimenter.addExperiment(exp);
            resultsWLadd.addResult(exp.getResults().getAccuracy());
            resultsWLadd.addResult(exp.getResults().getF1());
            
            System.out.println("Running WL, it " + i + " on " + dataset.getLabel());
          }
        }


        
        resultsSTFadd.newRow(dataset.getLabel() + " IntersectionFullSubTree");
        for (int i = 0; i < 4; i++) {


          if (experimenter.hasSpace()) {    
            int fileId = (int) (Math.random() * 100000000);  
            File file = new File(DATA_DIR + fileId + "_" + "IntersectionFullSubTree" + "_" + i + ".txt");
            exp = new PropertyPredictionExperiment(new PropertyPredictionDataSet(dataset), new IntersectionSubTreeKernel(i, 1), seeds, cs, new FileOutputStream(file));
            experimenter.addExperiment(exp);
            resultsSTFadd.addResult(exp.getResults().getAccuracy());
            resultsSTFadd.addResult(exp.getResults().getF1());
            
            System.out.println("Running STF, it " + i + " on " + dataset.getLabel());
          }


        }


        resultsSTPadd.newRow(dataset.getLabel() + " IntersectionPartialSubTree");
        for (int i = 0; i < 4; i++) {
          if (experimenter.hasSpace()) {    
            int fileId = (int) (Math.random() * 100000000);  
            File file = new File(DATA_DIR + fileId + "_" + "IntersectionPartialSubTree" + "_" + i + ".txt");
            exp = new PropertyPredictionExperiment(new PropertyPredictionDataSet(dataset), new IntersectionPartialSubTreeKernel(i, 0.01), seeds, cs, new FileOutputStream(file));
            experimenter.addExperiment(exp);
            resultsSTPadd.addResult(exp.getResults().getAccuracy());
            resultsSTPadd.addResult(exp.getResults().getF1());
            
            System.out.println("Running STP, it " + i + " on " + dataset.getLabel());
          }
        }
        
        resultsIGPadd.newRow(dataset.getLabel() + " IntersectionGraphPath");
        for (int i = 1; i < 3; i++) {
          if (experimenter.hasSpace()) {    
            int fileId = (int) (Math.random() * 100000000);  
            File file = new File(DATA_DIR + fileId + "_" + "IntersectionGraphPath" + "_" + i + ".txt");
            exp = new PropertyPredictionExperiment(new PropertyPredictionDataSet(dataset), new IntersectionGraphPathKernel(i, 1), seeds, cs, new FileOutputStream(file));
            experimenter.addExperiment(exp);
            resultsIGPadd.addResult(exp.getResults().getAccuracy());
            resultsIGPadd.addResult(exp.getResults().getF1());
            
            System.out.println("Running IGP, it " + i + " on " + dataset.getLabel());
          }
        }        


        resultsIGWadd.newRow(dataset.getLabel() + " IntersectionGraphWalk");
        for (int i = 1; i < 3; i++) {
          if (experimenter.hasSpace()) {    
            int fileId = (int) (Math.random() * 100000000);  
            File file = new File(DATA_DIR + fileId + "_" + "IntersectionGraphWalk" + "_" + i + ".txt");
            exp = new PropertyPredictionExperiment(new PropertyPredictionDataSet(dataset), new IntersectionGraphWalkKernel(i, 1), seeds, cs, new FileOutputStream(file));
            experimenter.addExperiment(exp);
            resultsIGWadd.addResult(exp.getResults().getAccuracy());
            resultsIGWadd.addResult(exp.getResults().getF1());
            
            System.out.println("Running IGW, it " + i + " on " + dataset.getLabel());
          }
        }
      }
      


      
      
      
    /***********
     * END OF EXPERIMENTER
     * 
     *  
     */
    } catch (Exception e) {
      e.printStackTrace();
    }


    experimenter.stop();


    while (expT.isAlive()) {
      try {
        Thread.sleep(1000);
      } catch (Exception e) {

View Full Code Here

    PropertyPredictionDataSet dataset;
    PropertyPredictionExperiment exp;


    List<ExperimentResults> results = new ArrayList<ExperimentResults>();
    
    Experimenter experimenter = new Experimenter(3);
    Thread expT = new Thread(experimenter);
    expT.setDaemon(true);
    expT.start();


    //double[][] results = new double[dataSetsParams.size()][3];


    int j = 0;
    for (PropertyPredictionDataSetParameters params : dataSetsParams) {
      dataset = DataSetFactory.createPropertyPredictionDataSet(params);
      dataset.removeSmallClasses(5);
      
      for (int i = 0; i < 3; i++) {


        if (experimenter.hasSpace()) {
          
          int fileId = (int) (Math.random() * 10000000);
          
          File file = new File("D:\\workspaces\\datasets\\aifb\\" + fileId + "_" + "IGP" + "_" + i + ".txt");
          //file.mkdirs();
          
          try {
            //exp = new PropertyPredictionExperiment(new PropertyPredictionDataSet(dataset), new IntersectionSubTreeKernel(i, 1), seeds, cs);
            exp = new PropertyPredictionExperiment(new PropertyPredictionDataSet(dataset), new WLSubTreeKernel(i), seeds, cs);
            
            //exp = new ClassificationExperiment(new GraphClassificationDataSet(dataset), new IntersectionGraphPathKernel(i, 1), seeds, cs, new FileOutputStream(file));
            experimenter.addExperiment(exp);
            results.add(exp.getResults());


          } catch (Exception e) {
            e.printStackTrace();
          }
          //exp = new ClassificationExperiment(dataset, new IntersectionSubTreeKernel(dataset.getGraphs(), dataset.getRootVertices(), i, 1), seeds, cs);
          //exp = new ClassificationExperiment(dataset, new IntersectionGraphPathKernel(dataset.getGraphs(), i, 1), seeds, cs);


          
          //results[j][i] = exp.getAccuracy();
        }
      }
      j++;
    }
    
    experimenter.stop();
    
    while (expT.isAlive()) {
      try {
        Thread.sleep(1000);
      } catch (Exception e) {

View Full Code Here

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