Examples of LibSVMParameters

org.data2semantics.proppred.learners.libsvm.LibSVMParameters
Wrapper class around the LibSVM svm_parameter object. We allow the choice of all the SVM algorithms implemented in libsvm. However, we only use the precomputed kernel setting and do not support the probability estimates setting. @author Gerben

Examples of org.data2semantics.proppred.learners.libsvm.LibSVMParameters


    int depth = 3;
    int iteration = 6;
    boolean inference = true;


    LibSVMParameters parms = new LibSVMParameters(LibSVMParameters.C_SVC, cs);
    ResultsTable resTable = new ResultsTable();


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

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Examples of org.data2semantics.proppred.learners.libsvm.LibSVMParameters

    int[] iterations = {0, 2, 4, 6};


    createAffiliationPredictionDataSet(1);




    LibSVMParameters parms = new LibSVMParameters(LibSVMParameters.C_SVC, cs);
    //parms.setEvalFunction(LibSVMParameters.F1);


    ResultsTable resTable = new ResultsTable();

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Examples of org.data2semantics.proppred.learners.libsvm.LibSVMParameters

    //int[] iterations2 = {0,2,4,6,8,10,12,14,16,18,20};
    int[] iterations  = {0,1,2,3,4,5};
    int[] iterations2 = {0,2,4,6,8,10};




    LibSVMParameters svmParms = new LibSVMParameters(LibSVMParameters.C_SVC, cs);
    svmParms.setNumFolds(10);


    LibLINEARParameters linParms = new LibLINEARParameters(LibLINEARParameters.SVC_DUAL, cs);
    linParms.setNumFolds(5);
    linParms.setSplitFraction((float) 0.7);
    linParms.setDoCrossValidation(false);

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Examples of org.data2semantics.proppred.learners.libsvm.LibSVMParameters


    int depth = 3;
    int iteration = 6;
    boolean inference = true;


    LibSVMParameters parms = new LibSVMParameters(LibSVMParameters.C_SVC, cs);
    ResultsTable resTable = new ResultsTable();


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

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Examples of org.data2semantics.proppred.learners.libsvm.LibSVMParameters

    int depth = 3;
    int[] iterations = {0, 2, 4, 6};


    dataset = new RDFFileDataSet(dataDir, RDFFormat.NTRIPLES);


    LibSVMParameters parms = new LibSVMParameters(LibSVMParameters.C_SVC, cs);


    ResultsTable resTable = new ResultsTable();
    resTable.setManWU(0.05);


    boolean inference = false;

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Examples of org.data2semantics.proppred.learners.libsvm.LibSVMParameters


    dataset = new RDFFileDataSet(dataDir, RDFFormat.NTRIPLES);
    createGeoDataSet(1, 1, "http://data.bgs.ac.uk/ref/Lexicon/hasLithogenesis");




    LibSVMParameters parms = new LibSVMParameters(LibSVMParameters.C_SVC, cs);
    //parms.setEvalFunction(LibSVM.F1);


    ResultsTable resTable = new ResultsTable();
    resTable.setDigits(2);

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Examples of org.data2semantics.proppred.learners.libsvm.LibSVMParameters

    evalFuncs.add(new Error());
    evalFuncs.add(new F1());


    List<Double> target = EvaluationUtils.createTarget(labels);


    LibSVMParameters svmParms = new LibSVMParameters(LibSVMParameters.C_SVC, cs);
    svmParms.setNumFolds(10);


    svmParms.setWeightLabels(EvaluationUtils.computeWeightLabels(target));
    svmParms.setWeights(EvaluationUtils.computeWeights(target));
    //---------


    //---------
    // Results Table
    ResultsTable resTable = new ResultsTable();

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Examples of org.data2semantics.proppred.learners.libsvm.LibSVMParameters

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


    LibSVMParameters svmParms = new LibSVMParameters(LibSVMParameters.C_SVC, cs);
    svmParms.setNumFolds(10);


    svmParms.setWeightLabels(EvaluationUtils.computeWeightLabels(target));
    svmParms.setWeights(EvaluationUtils.computeWeights(target));


    ResultsTable resTable = new ResultsTable();
    resTable.setDigits(2);


    List<Statement> allStmts = dataset.getStatements(null, null, null, inference);

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Examples of org.data2semantics.proppred.learners.libsvm.LibSVMParameters

    for (int i : depths) {      
      for (int it : iterations) {
        resTable.newRow("");
        
        
        LibSVMParameters parms = new LibSVMParameters(LibSVMParameters.C_SVC, cs);
        KernelExperiment<RDFGraphKernel> exp = new RDFOldKernelExperiment(new RDFWLSubTreeKernel(it, i, inference, true), seeds, parms, dataset, instances, labels, blackList);
        
        System.out.println("Running WL RDF: " + i + " " + it);
        exp.run();

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Examples of org.data2semantics.proppred.learners.libsvm.LibSVMParameters

    evalFuncs.add(new Error());
    evalFuncs.add(new F1());


    List<Double> target = EvaluationUtils.createTarget(labels);


    LibSVMParameters svmParms = new LibSVMParameters(LibSVMParameters.C_SVC, cs);
    svmParms.setNumFolds(10);


    svmParms.setWeightLabels(EvaluationUtils.computeWeightLabels(target));
    svmParms.setWeights(EvaluationUtils.computeWeights(target));
    //---------






    //-------

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