Package org.data2semantics.exp.utils

Examples of org.data2semantics.exp.utils.RDFLinearKernelExperiment

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        //k.setIgnoreLiterals(false);
       
        //RDFOldKernelExperiment exp = new RDFOldKernelExperiment(k, seeds, svmParms, dataset, instances, labels, blackList);

       
        RDFLinearKernelExperiment exp = new RDFLinearKernelExperiment(k, seeds, linParms, dataset, instances, targets, blackList, evalFuncs);
        exp.setDoCV(true);
        exp.setDoTFIDF(true);

        System.out.println("Running WL RDF text: " + d + " " + it);
        exp.run();

        for (Result res : exp.getResults()) {
          resTable.addResult(res);
        }
      }
    }
    System.out.println(resTable);

    /*
    for (int d : depths) {
      resTable.newRow("");
      for (int it : iterations) {
        List<RDFFeatureVectorKernel> kernels = new ArrayList<RDFFeatureVectorKernel>();
        RDFWLSubTreeKernel k = new RDFWLSubTreeKernel(it, d, inference, false);
        k.setIgnoreLiterals(false);
       
        kernels.add(k);
        kernels.add(new RDFSimpleTextKernel(d, inference, false));

        RDFFeatureVectorKernel kernel = new RDFCombinedKernel(kernels, false);

        RDFLinearKernelExperiment exp = new RDFLinearKernelExperiment(kernel, seeds, linParms, dataset, instances, targets, blackList, evalFuncs);
        exp.setDoCV(true);
        exp.setDoTFIDF(true);

        System.out.println("Running Text + WL RDF: " + d + " " + it);
        exp.run();

        for (Result res : exp.getResults()) {
          resTable.addResult(res);
        }
      }
    }
    */

   
    /*
    for (int d : depths) {
      resTable.newRow("");

      RDFOldKernelExperiment exp = new RDFOldKernelExperiment(new RDFIntersectionTreeEdgeVertexPathKernel(d, false, inference, true), seeds, svmParms, dataset, instances, labels, blackList);

     
      //RDFLinearKernelExperiment exp = new RDFLinearKernelExperiment(new RDFIntersectionTreeEdgeVertexPathKernel(d, false, inference, true), seeds, linParms, dataset, instances, targets, blackList, evalFuncs);
      //exp.setDoCV(true);
      //exp.setDoTFIDF(false);

      System.out.println("Running Edge Vertex Path: " + d);
      exp.run();

      for (Result res : exp.getResults()) {
        resTable.addResult(res);
      }

    }
    System.out.println(resTable);
    */


    for (int d : depths) {
      resTable.newRow("ITP BoW, depth="+d);

      //RDFOldKernelExperiment exp = new RDFOldKernelExperiment(new RDFIntersectionTreeEdgeVertexPathWithTextKernel(d, false, inference, false), seeds, svmParms, dataset, instances, labels, blackList);

     
      RDFLinearKernelExperiment exp = new RDFLinearKernelExperiment(new RDFIntersectionTreeEdgeVertexPathWithTextKernel(d, false, inference, false), seeds, linParms, dataset, instances, targets, blackList, evalFuncs);
      exp.setDoCV(true);
//      exp.setDoBinary(true);
      exp.setDoTFIDF(true);

      System.out.println("Running Edge Vertex Path with Text: " + d);
      exp.run();

      for (Result res : exp.getResults()) {
        resTable.addResult(res);
      }

    }
    System.out.println(resTable);
View Full Code Here
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            weights[(int) label - 1] = 1 / counts.get(label);
          }
          linParms.setWeightLabels(wLabels);
          linParms.setWeights(weights);

          RDFLinearKernelExperiment exp = new RDFLinearKernelExperiment(new RDFWLSubTreeKernel(it, i, inference, true), seeds2, linParms, dataset, instances, target, blackList, evalFuncs);

          System.out.println("Running WL RDF: " + i + " " + it);
          exp.setDoCV(true);
          exp.run();
          res.add(exp.getResults());
        }

        for (Result res2 : Result.mergeResultLists(res)) {
          resTable.addResult(res2);
        }
      }
    }
    System.out.println(resTable);


    for (int i : depths) { 
      resTable.newRow("WL RDF BoW, depth="+i); 
      for (int it : iterations) {

        List<List<Result>> res = new ArrayList<List<Result>>();
        for (long seed : seeds) {
          long[] seeds2 = {seed};
         
          createGeoDataSet((int)(1000 * fraction), fraction, seed, "http://data.bgs.ac.uk/ref/Lexicon/hasTheme");
          List<Double> target = EvaluationUtils.createTarget(labels);

          LibLINEARParameters linParms = new LibLINEARParameters(LibLINEARParameters.SVC_DUAL, cs);
          linParms.setDoCrossValidation(true);
          linParms.setNumFolds(5);

          Map<Double, Double> counts = EvaluationUtils.computeClassCounts(target);
          int[] wLabels = new int[counts.size()];
          double[] weights = new double[counts.size()];

          for (double label : counts.keySet()) {
            wLabels[(int) label - 1] = (int) label;
            weights[(int) label - 1] = 1 / counts.get(label);
          }
          linParms.setWeightLabels(wLabels);
          linParms.setWeights(weights);

          RDFLinearKernelExperiment exp = new RDFLinearKernelExperiment(new RDFWLSubTreeWithTextKernel(it, i, inference, true), seeds2, linParms, dataset, instances, target, blackList, evalFuncs);

          System.out.println("Running WL RDF with text: " + i + " " + it);
          exp.setDoCV(true);
          exp.run();
          res.add(exp.getResults());
        }

        for (Result res2 : Result.mergeResultLists(res)) {
          resTable.addResult(res2);
        }
      }
    }
    System.out.println(resTable);
   
   
    for (int i : depths) { 
      resTable.newRow("ITP, depth="+i); 

      List<List<Result>> res = new ArrayList<List<Result>>();
      for (long seed : seeds) {
        long[] seeds2 = {seed};
        createGeoDataSet((int)(1000 * fraction), fraction, seed, "http://data.bgs.ac.uk/ref/Lexicon/hasTheme");
        List<Double> target = EvaluationUtils.createTarget(labels);

        LibLINEARParameters linParms = new LibLINEARParameters(LibLINEARParameters.SVC_DUAL, cs);
        linParms.setDoCrossValidation(true);
        linParms.setNumFolds(5);

        Map<Double, Double> counts = EvaluationUtils.computeClassCounts(target);
        int[] wLabels = new int[counts.size()];
        double[] weights = new double[counts.size()];

        for (double label : counts.keySet()) {
          wLabels[(int) label - 1] = (int) label;
          weights[(int) label - 1] = 1 / counts.get(label);
        }
        linParms.setWeightLabels(wLabels);
        linParms.setWeights(weights);

        RDFLinearKernelExperiment exp = new RDFLinearKernelExperiment(new RDFIntersectionTreeEdgeVertexPathKernel(i, false, inference, true), seeds2, linParms, dataset, instances, target, blackList, evalFuncs);

        System.out.println("Running EVP: " + i);
        exp.setDoCV(true);
        exp.run();
        res.add(exp.getResults());
      }

      for (Result res2 : Result.mergeResultLists(res)) {
        resTable.addResult(res2);
      }
    }
    System.out.println(resTable);
   
    for (int i : depths) { 
      resTable.newRow("ITP BoW, depth="+i); 

      List<List<Result>> res = new ArrayList<List<Result>>();
      for (long seed : seeds) {
        long[] seeds2 = {seed};
        createGeoDataSet((int)(1000 * fraction), fraction, seed, "http://data.bgs.ac.uk/ref/Lexicon/hasTheme");
        List<Double> target = EvaluationUtils.createTarget(labels);

        LibLINEARParameters linParms = new LibLINEARParameters(LibLINEARParameters.SVC_DUAL, cs);
        linParms.setDoCrossValidation(true);
        linParms.setNumFolds(5);

        Map<Double, Double> counts = EvaluationUtils.computeClassCounts(target);
        int[] wLabels = new int[counts.size()];
        double[] weights = new double[counts.size()];

        for (double label : counts.keySet()) {
          wLabels[(int) label - 1] = (int) label;
          weights[(int) label - 1] = 1 / counts.get(label);
        }
        linParms.setWeightLabels(wLabels);
        linParms.setWeights(weights);

        RDFLinearKernelExperiment exp = new RDFLinearKernelExperiment(new RDFIntersectionTreeEdgeVertexPathWithTextKernel(i, false, inference, false), seeds2, linParms, dataset, instances, target, blackList, evalFuncs);

        System.out.println("Running EVP with text: " + i);
        exp.setDoCV(true);
        exp.setDoTFIDF(true);
        exp.run();
        res.add(exp.getResults());
      }

      for (Result res2 : Result.mergeResultLists(res)) {
        resTable.addResult(res2);
      }
    }
    System.out.println(resTable);

   

    for (int i : depths) { 
      resTable.newRow("IST, depth="+i); 

      List<List<Result>> res = new ArrayList<List<Result>>();
      for (long seed : seeds) {
        long[] seeds2 = {seed};
        createGeoDataSet((int)(1000 * fraction), fraction, seed, "http://data.bgs.ac.uk/ref/Lexicon/hasTheme");
        List<Double> target = EvaluationUtils.createTarget(labels);

        LibSVMParameters svmParms = new LibSVMParameters(LibSVMParameters.C_SVC, cs);
        svmParms.setNumFolds(5);


        KernelExperiment<RDFGraphKernel> exp = new RDFOldKernelExperiment(new RDFIntersectionSubTreeKernel(i, 1, inference, true), seeds2, svmParms, dataset, instances, labels, blackList);

        System.out.println("Running IST: " + i);
        exp.run();
        res.add(exp.getResults());
      }

      for (Result res2 : Result.mergeResultLists(res)) {
        resTable.addResult(res2);
      }
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    evalFuncs.add(new Accuracy());
    evalFuncs.add(new F1());
    long[] seeds2={seed};
    System.out.println(dataset + " " + labels.size() + " " + instances.size() + " " + blackList.size());
   
    RDFLinearKernelExperiment exp = new RDFLinearKernelExperiment(new RDFWLSubTreeKernel(iteration, depth, true, true), seeds2, linParms, dataset, instances, target, blackList, evalFuncs);
   
    exp.setDoCV(true);
    exp.run();
   
    System.out.println(exp.getResults());
  }
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    */
   
    for (int depth : depths) {
      resTable.newRow("");
      for (int it : iterations) {
        RDFLinearKernelExperiment exp = new RDFLinearKernelExperiment(new RDFWLSubTreeKernel(it, depth, inference, normalize), seeds, linParms, dataset, instances, targets, blackList, evalFuncs);

        System.out.println("Running WL RDF: " + depth + " " + it);
        exp.setDoCV(true);
        exp.setDoTFIDF(tfidf);
        exp.run();

        for (Result res : exp.getResults()) {
          resTable.addResult(res);
        }
      }
    }
    System.out.println(resTable);

   
System.out.println(resTable);
   
    for (int depth : depths) {
      resTable.newRow("");
      for (int it : iterations) {
        List<RDFFeatureVectorKernel> kernels = new ArrayList<RDFFeatureVectorKernel>();
        RDFWLSubTreeKernel k = new RDFWLSubTreeKernel(it, depth, inference, normalize);
       
        kernels.add(k);
        kernels.add(new RDFSimpleTextKernel(depth, inference, normalize));

        RDFFeatureVectorKernel kernel = new RDFCombinedKernel(kernels, normalize);

       
        RDFLinearKernelExperiment exp = new RDFLinearKernelExperiment(kernel, seeds, linParms, dataset, instances, targets, blackList, evalFuncs);

        System.out.println("Running WL RDF  + text: " + depth + " " + it);
        exp.setDoCV(true);
        exp.setDoTFIDF(tfidf);
        exp.run();

        for (Result res : exp.getResults()) {
          resTable.addResult(res);
        }
      }
    }
    System.out.println(resTable);
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      for (int i : depths) {     
        for (int it : iterations) {
          resTable.newRow(""); 

          KernelExperiment<RDFFeatureVectorKernel> exp = new RDFLinearKernelExperiment(new RDFWLSubTreeKernel(it, i, inference, true), seeds, linParms, dataset, instances, target, blackList, evalFuncs);
       
          System.out.println("Running WL RDF: " + i + " " + it);
          exp.run();

          for (Result res : exp.getResults()) {
            resTable.addResult(res);
          } 
        }
      }
     

      for (int i : depths) {     
        //for (int it : iterations) {
          resTable.newRow(""); 

          //KernelExperiment<RDFFeatureVectorKernel> exp = new RDFLinearKernelExperiment(new RDFWLSubTreeKernel(it, i, inference, true), seeds, linParms, dataset, instances, target, blackList, evalFuncs);

          KernelExperiment<RDFFeatureVectorKernel> exp = new RDFLinearKernelExperiment(new RDFIntersectionTreeEdgeVertexPathKernel(i, false, inference, true), seeds, linParms, dataset, instances, target, blackList, evalFuncs);

         
          System.out.println("Running EVP: " + i);
          //System.out.println("Running WL RDF: " + i + " " + it);
          exp.run();

          for (Result res : exp.getResults()) {
            resTable.addResult(res);
          } 
        }
      //}
    }
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          }
          linParms.setWeightLabels(wLabels);
          linParms.setWeights(weights);


          RDFLinearKernelExperiment exp = new RDFLinearKernelExperiment(new RDFWLSubTreeKernel(it, d, inference, true), s2, linParms, dataset, instances, targets, blackList, evalFuncs);
          res.add(exp.getResults());

          System.out.println("Running WL RDF: " + d + " " + it);
          exp.run();
        }
        for (Result res2 : Result.mergeResultLists(res)) {
          resTable.addResult(res2);
        }
      }
View Full Code Here
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    for (int i : depths) {     
      for (int it : iterations) {
        resTable.newRow("");

        LibLINEARParameters linParms = new LibLINEARParameters(LibLINEARParameters.SVC_DUAL, cs);
        KernelExperiment<RDFFeatureVectorKernel> exp = new RDFLinearKernelExperiment(new RDFWLSubTreeKernel(it, i, inference, true), seeds, linParms, dataset, instances, target, blackList, evalFuncs);

        System.out.println("Running WL RDF: " + i + " " + it);
        exp.run();

        for (Result res : exp.getResults()) {
          resTable.addResult(res);
        } 
      }
    }
    System.out.println(resTable);

    for (int i : depths) {     
      resTable.newRow("");

      LibLINEARParameters linParms = new LibLINEARParameters(LibLINEARParameters.SVC_DUAL, cs);
      KernelExperiment<RDFFeatureVectorKernel> exp = new RDFLinearKernelExperiment(new RDFIntersectionTreeEdgeVertexPathKernel(i, false, inference, true), seeds, linParms, dataset, instances, target, blackList, evalFuncs);

      System.out.println("Running EVP: " + i);
      exp.run();

      for (Result res : exp.getResults()) {
        resTable.addResult(res);
      } 
    }
    System.out.println(resTable);
   
    for (int i : depths) {     
      resTable.newRow("");

      LibSVMParameters svmParms = new LibSVMParameters(LibSVMParameters.C_SVC, cs);
   
      KernelExperiment<RDFGraphKernel> exp = new RDFOldKernelExperiment(new RDFIntersectionSubTreeKernel(i, 1, inference, true), seeds, svmParms, dataset, instances, labels, blackList);

      System.out.println("Running IST: " + i);
      exp.run();

      for (Result res : exp.getResults()) {
        resTable.addResult(res);
      } 
    }

View Full Code Here
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Related Classes of org.data2semantics.exp.utils.RDFLinearKernelExperiment

  • org.data2semantics.exp.CompareLinearKernelsExperiment
  • org.data2semantics.exp.dmold.DMoLDThemeExperiment
  • org.data2semantics.exp.dmold.Task2Experiment
  • org.data2semantics.exp.FullClassExperiment
  • org.data2semantics.exp.FullThemeExperiment
  • org.data2semantics.exp.GoldenDemoExperiment
  • org.data2semantics.modules.LinearKernelExperimentModule
  • org.data2semantics.proppred.kernels.rdfgraphkernels.RDFWLSubTreeKernel
  • org.data2semantics.proppred.learners.liblinear.LibLINEARModel
  • java.util.Random
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