Package org.data2semantics.exp.old.utils.datasets

Examples of org.data2semantics.exp.old.utils.datasets.GeneralPredictionDataSetParameters

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      res.setLabel("runtime");
      for (long seed : seeds) {

        createAffiliationPredictionDataSet(frac,seed);
        tic = System.currentTimeMillis();
        PropertyPredictionDataSet ds = DataSetFactory.createPropertyPredictionDataSet(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 3, false, true));
        toc = System.currentTimeMillis();

        KernelExperiment<GraphKernel> exp = new GraphKernelRunTimeExperiment(new ECML2013WLSubTreeKernel(iteration), seeds, parms, ds.getGraphs(), labels);

        System.out.println("Running WL: " + frac);
        exp.run();
        res.addResult(exp.getResults().get(0));

        double[] comps = {2 * (toc-tic) + res.getScore()};
        Result resC = new Result(comps,"comp time 2"); 
        res.addResult(resC);
      }

      resTable.addResult(res);
    }
    /*
    resTable.newRow("");
    for (double frac : fractions) {
      createAffiliationPredictionDataSet(frac);
      tic = System.currentTimeMillis();
      PropertyPredictionDataSet ds = DataSetFactory.createPropertyPredictionDataSet(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 3, false, true));
      toc = System.currentTimeMillis();


      KernelExperiment<GraphKernel> exp = new GraphKernelExperiment(new ECML2013IntersectionGraphPathKernel(2,1), seeds, parms, ds.getGraphs(), labels);

      System.out.println("Running IGP: " + frac);
      exp.run();

      double[] comps =  {0,0};
  comps[0] = 2*(toc-tic) + exp.getResults().get(exp.getResults().size()-1).getScore();
      comps[1] = 2*(toc-tic) + exp.getResults().get(exp.getResults().size()-1).getScore();
          Result resC = new Result(comps,"comp time 2"); 
      exp.getResults().get(exp.getResults().size()-1).addResult(resC);

      resTable.addResult(exp.getResults().get(exp.getResults().size()-1));
    }*/


    resTable.newRow("IGW");
    for (double frac : fractions) {

      Result res = new Result();
      res.setLabel("runtime");
      for (long seed : seeds) {
        createAffiliationPredictionDataSet(frac,seed);
        tic = System.currentTimeMillis();
        PropertyPredictionDataSet ds = DataSetFactory.createPropertyPredictionDataSet(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 3, false, true));
        toc = System.currentTimeMillis();

        KernelExperiment<GraphKernel> exp = new GraphKernelRunTimeExperiment(new ECML2013IntersectionGraphWalkKernel(2,1), seeds, parms, ds.getGraphs(), labels);

        System.out.println("Running IGW: " + frac);
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    List<GeneralPredictionDataSetParameters> dataSetsParams = new ArrayList<GeneralPredictionDataSetParameters>();

    dataSetsParams.add(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 1, false, false));
    dataSetsParams.add(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 2, false, false));
    dataSetsParams.add(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 3, false, false));

    dataSetsParams.add(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 1, false, true));
    dataSetsParams.add(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 2, false, true));
    dataSetsParams.add(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 3, false, true));


    int[] iterationsIG = {1,2};
    long tic, toc;
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    double[] cs = {0.001, 0.01, 0.1, 1, 10, 100, 1000}; 
    int maxClassSize = 50;


 
    dataSetsParams.add(new GeneralPredictionDataSetParameters(testSetA, blacklists, instances, 1, false, false));
    dataSetsParams.add(new GeneralPredictionDataSetParameters(testSetA, blacklists, instances, 2, false, false));
    dataSetsParams.add(new GeneralPredictionDataSetParameters(testSetA, blacklists, instances, 3, false, false));
    //dataSetsParams.add(new GeneralPredictionDataSetParameters(testSetA, blacklists, instances, 4, false, false));
   
   
    dataSetsParams.add(new GeneralPredictionDataSetParameters(testSetA, blacklists, instances, 1, false, true));
    dataSetsParams.add(new GeneralPredictionDataSetParameters(testSetA, blacklists, instances, 2, false, true));
    dataSetsParams.add(new GeneralPredictionDataSetParameters(testSetA, blacklists, instances, 3, false, true));
   
    dataSetsParams.add(new GeneralPredictionDataSetParameters(testSetA, blacklists, instances, 1, true, false));
    dataSetsParams.add(new GeneralPredictionDataSetParameters(testSetA, blacklists, instances, 2, true, false));
    dataSetsParams.add(new GeneralPredictionDataSetParameters(testSetA, blacklists, instances, 1, true, true));
    dataSetsParams.add(new GeneralPredictionDataSetParameters(testSetA, blacklists, instances, 2, true, true));
   
   


   
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      Result res = new Result();
      res.setLabel("runtime");
      for (long seed : seeds) {
        createGeoDataSet(seed,frac,6,"http://data.bgs.ac.uk/ref/Lexicon/hasLithogenesis");
        tic = System.currentTimeMillis();
        PropertyPredictionDataSet ds = DataSetFactory.createPropertyPredictionDataSet(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 3, false, true));
        toc = System.currentTimeMillis();

        KernelExperiment<GraphKernel> exp = new GraphKernelRunTimeExperiment(new ECML2013WLSubTreeKernel(iteration), seeds, parms, ds.getGraphs(), labels);

        System.out.println("Running WL: " + frac);
        exp.run();

        res.addResult(exp.getResults().get(0));

        double[] comps = {2 * (toc-tic) + res.getScore()};
        Result resC = new Result(comps,"comp time 2"); 
        res.addResult(resC);
      }

      resTable.addResult(res); 
    }

    /*
    resTable.newRow("");
    for (double frac : fractions) {
      createGeoDataSet(11,frac,"http://data.bgs.ac.uk/ref/Lexicon/hasLithogenesis");
      tic = System.currentTimeMillis();
      PropertyPredictionDataSet ds = DataSetFactory.createPropertyPredictionDataSet(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 3, false, true));
      toc = System.currentTimeMillis();


      KernelExperiment<GraphKernel> exp = new GraphKernelExperiment(new ECML2013IntersectionGraphPathKernel(2,1), seeds, parms, ds.getGraphs(), labels);

      System.out.println("Running IGP: " + frac);
      exp.run();

      double[] comps =  {0,0};
      comps[0] = 2*(toc-tic) + exp.getResults().get(exp.getResults().size()-1).getScore();
      comps[1] = 2*(toc-tic) + exp.getResults().get(exp.getResults().size()-1).getScore();
      Result resC = new Result(comps,"comp time 2"); 
      exp.getResults().get(exp.getResults().size()-1).addResult(resC);


      resTable.addResult(exp.getResults().get(exp.getResults().size()-1)); 
    }
     */

    resTable.newRow("IGW");
    for (double frac : fractions) {

      Result res = new Result();
      res.setLabel("runtime");
      for (long seed : seeds) {
        createGeoDataSet(seed,frac,6,"http://data.bgs.ac.uk/ref/Lexicon/hasLithogenesis");
        tic = System.currentTimeMillis();
        PropertyPredictionDataSet ds = DataSetFactory.createPropertyPredictionDataSet(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 3, false, true));
        toc = System.currentTimeMillis();


        KernelExperiment<GraphKernel> exp = new GraphKernelRunTimeExperiment(new ECML2013IntersectionGraphWalkKernel(2,1), seeds, parms, ds.getGraphs(), labels);

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    List<GeneralPredictionDataSetParameters> dataSetsParams = new ArrayList<GeneralPredictionDataSetParameters>();

    dataSetsParams.add(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 1, false, false));
    dataSetsParams.add(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 2, false, false));
    dataSetsParams.add(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 3, false, false));

    dataSetsParams.add(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 1, false, true));
    dataSetsParams.add(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 2, false, true));
    dataSetsParams.add(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 3, false, true));


    int[] iterationsIG = {1,2};
    long tic, toc;
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    resTable.newRow("WL FV");
    for (double frac : fractionsSlow) {
      createGeoDataSet((int)(1000 * frac), frac, seed, "http://data.bgs.ac.uk/ref/Lexicon/hasUnitClass");   
      tic = System.currentTimeMillis();
      PropertyPredictionDataSet ds = DataSetFactory.createPropertyPredictionDataSet(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 3, false, true));
      toc = System.currentTimeMillis();
      double dsComp = toc-tic;
     
      FeatureVectorKernel k = new WLSubTreeKernel(6,true);
     
      System.out.println("WL: " + frac);
      tic = System.currentTimeMillis();
      k.computeFeatureVectors(ds.getGraphs());
      toc = System.currentTimeMillis();
      double[] comp = {(toc-tic) + dsComp};
      Result res = new Result(comp, "comp time");
      resTable.addResult(res);
    }   
    System.out.println(resTable);
   
   
    resTable.newRow("WL Kernel");
    for (double frac : fractionsSlow) {
      createGeoDataSet((int)(1000 * frac), frac, seed, "http://data.bgs.ac.uk/ref/Lexicon/hasUnitClass");   
      tic = System.currentTimeMillis();
      PropertyPredictionDataSet ds = DataSetFactory.createPropertyPredictionDataSet(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 3, false, true));
      toc = System.currentTimeMillis();
      double dsComp = toc-tic;
     
      GraphKernel k = new WLSubTreeKernel(6,true);
     
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    //for (double frac : fractionsSlow) {
      comp = new double[seeds.length];
      for (int i = 0; i < seeds.length; i++) {
        createGeoDataSet((int)(1000 * frac), frac, seeds[i], "http://data.bgs.ac.uk/ref/Lexicon/hasTheme");   
        tic = System.currentTimeMillis();
        PropertyPredictionDataSet ds = DataSetFactory.createPropertyPredictionDataSet(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 3, false, true));
        toc = System.currentTimeMillis();
        double dsComp = toc-tic;

        FeatureVectorKernel k = new WLSubTreeKernel(6,true);

        System.out.println("WL: " + frac);
        tic = System.currentTimeMillis();
        k.computeFeatureVectors(ds.getGraphs());
        toc = System.currentTimeMillis();
        comp[i] = (toc-tic) + dsComp;
      }
      res = new Result(comp, "comp time");
      resTable.addResult(res);
    //}   
    //System.out.println(resTable);


    //resTable.newRow("WL Kernel");
    //for (double frac : fractionsSlow) {
      comp = new double[seeds.length];
      for (int i = 0; i < seeds.length; i++) {
        createGeoDataSet((int)(1000 * frac), frac, seeds[i], "http://data.bgs.ac.uk/ref/Lexicon/hasTheme");   
        tic = System.currentTimeMillis();
        PropertyPredictionDataSet ds = DataSetFactory.createPropertyPredictionDataSet(new GeneralPredictionDataSetParameters(dataset, blackLists, instances, 3, false, true));
        toc = System.currentTimeMillis();
        double dsComp = toc-tic;

        GraphKernel k = new WLSubTreeKernel(6,true);

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Related Classes of org.data2semantics.exp.old.utils.datasets.GeneralPredictionDataSetParameters

  • org.data2semantics.exp.ecml2013.AffiliationCompareExperiment
  • org.data2semantics.exp.ecml2013.GeoCompareExperiment
  • org.data2semantics.exp.FullClassRunningTimeExperiment
  • org.data2semantics.exp.FullThemeRunningTimeExperiment
  • org.data2semantics.exp.old.BibleReligionPredictionExperiment
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