Examples of de.bwaldvogel.liblinear.Problem

de.bwaldvogel.liblinear.Problem

Describes the problem

For example, if we have the following training data:

 LABEL       ATTR1   ATTR2   ATTR3   ATTR4   ATTR5 -----       -----   -----   -----   -----   ----- 1           0       0.1     0.2     0       0 2           0       0.1     0.3    -1.2     0 1           0.4     0       0       0       0 2           0       0.1     0       1.4     0.5 3          -0.1    -0.2     0.1     1.1     0.1 and bias = 1, then the components of problem are: l = 5 n = 6 y -> 1 2 1 2 3 x -> [ ] -> (2,0.1) (3,0.2) (6,1) (-1,?) [ ] -> (2,0.1) (3,0.3) (4,-1.2) (6,1) (-1,?) [ ] -> (1,0.4) (6,1) (-1,?) [ ] -> (2,0.1) (4,1.4) (5,0.5) (6,1) (-1,?) [ ] -> (1,-0.1) (2,-0.2) (3,0.1) (4,1.1) (5,0.1) (6,1) (-1,?)


  private static Problem createProblemTrainSplit(Problem problem, float splitFrac) {
    int foldStart = 0; 
    int foldEnd   = Math.round(((float) problem.l) * splitFrac);


    Problem prob = new Problem();
    prob.y = Arrays.copyOfRange(problem.y, foldStart, foldEnd);
    prob.x = Arrays.copyOfRange(problem.x, foldStart, foldEnd);
    prob.l = foldEnd;
    prob.n = problem.n;

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  private static Problem createProblemTestSplit(Problem problem, float splitFrac) {
    int foldStart = Math.round(((float) problem.l) * splitFrac); 
    int foldEnd   = problem.l;


    Problem prob = new Problem();
    prob.y = Arrays.copyOfRange(problem.y, foldStart, foldEnd);
    prob.x = Arrays.copyOfRange(problem.x, foldStart, foldEnd);
    prob.l = prob.y.length;
    prob.n = problem.n;

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  private static Problem createProblemTrainFold(Problem problem, int numberOfFolds, int fold) {
    int foldStart = Math.round((problem.x.length / ((float) numberOfFolds)) * ((float) fold - 1));
    int foldEnd   = Math.round((problem.x.length / ((float) numberOfFolds)) * ((float) fold));
    int foldLength = (foldEnd-foldStart);


    Problem prob = new Problem();
    prob.y = new double[problem.x.length - foldLength];
    prob.x = new FeatureNode[problem.x.length - foldLength][];
    prob.l = problem.x.length - foldLength;
    prob.n = problem.n;

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     */
    protected Problem getProblem(FeatureNode[][] vx, int[] vy, int max_index) {


        if (vx.length != vy.length) throw new IllegalArgumentException("vx and vy must have same size");


        Problem problem = new Problem();


        problem.l = vy.length;
        problem.n = max_index;
        problem.bias = getBias();
        problem.x = vx;

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Related Classes of de.bwaldvogel.liblinear.Problem

org.data2semantics.proppred.learners.liblinear.LibLINEAR

org.maltparserx.ml.lib.LibLinear

org.maltparserx.ml.liblinear.Liblinear

weka.classifiers.functions.LibLINEAR

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