Example usage for weka.core Instance numAttributes

Introduction

In this page you can find the example usage for weka.core Instance numAttributes.

Prototype

public int numAttributes();

Source Link

Document

Returns the number of attributes.

Usage

From source file:de.ugoe.cs.cpdp.dataprocessing.TransferComponentAnalysis.java

License:Apache License

/**
 * <p>/*from   w  w w.  jav  a  2s  .c  o  m*/
 * calculates the linear kernel function between two instances
 * </p>
 *
 * @param x1
 *            first instance
 * @param x2
 *            second instance
 * @return kernel value
 */
private double linearKernel(Instance x1, Instance x2) {
    double value = 0.0d;
    for (int j = 0; j < x1.numAttributes(); j++) {
        if (j != x1.classIndex()) {
            value += x1.value(j) * x2.value(j);
        }
    }
    return value;
}

From source file:de.ugoe.cs.cpdp.util.WekaUtils.java

License:Apache License

/**
 * <p>/* w  w  w . j a v a2  s .  c  o  m*/
 * Adoption of the Hamming difference to numerical values, i.e., basically a count of different
 * metric values.
 * </p>
 *
 * @param inst1
 *            first instance to be compared
 * @param inst2
 *            second instance to be compared
 * @return the distance
 */
public static double hammingDistance(Instance inst1, Instance inst2) {
    double distance = 0.0;
    for (int j = 0; j < inst1.numAttributes(); j++) {
        if (j != inst1.classIndex()) {
            if (inst1.value(j) != inst2.value(j)) {
                distance += 1.0;
            }
        }
    }
    return distance;
}

From source file:de.ugoe.cs.cpdp.util.WekaUtils.java

License:Apache License

/**
 * <p>//  w  ww.j  a  v a  2s . c o  m
 * Returns a double array of the values without the classification.
 * </p>
 *
 * @param instance
 *            the instance
 * @return double array
 */
public static double[] instanceValues(Instance instance) {
    double[] values = new double[instance.numAttributes() - 1];
    int k = 0;
    for (int j = 0; j < instance.numAttributes(); j++) {
        if (j != instance.classIndex()) {
            values[k] = instance.value(j);
            k++;
        }
    }
    return values;
}

From source file:de.unidue.langtech.grading.tc.ClusterExemplarTask.java

License:Open Source License

private double distance(Instance i1, Instance i2) {
    double dist = 0.0;
    for (int i = 0; i < i1.numAttributes(); i++) {
        dist += Math.abs(i1.value(i) - i2.value(i));
    }//from  w w  w.  j a v a2  s.  com
    return dist / i1.numAttributes();
}

From source file:de.uniheidelberg.cl.swp.mlprocess.AblationTesting.java

License:Apache License

/**
 * Determines the attribute value for a Instance object and the specified attribute name.
 * /*from   w w  w .j a  va 2s . c  om*/
 * @param inst The instance object from which the value is extracted.
 * @param featureName The name of the attribute.
 * @return A double representation of the value used by WEKA.
 */
private double getAttributeValue(Instance inst, String featureName) {
    for (int i = 0; i < inst.numAttributes(); i++) {
        if (inst.attribute(i).name().equals(featureName))
            return inst.value(i);
    }
    return 0;
}

From source file:de.uniheidelberg.cl.swp.mlprocess.MLProcess.java

License:Apache License

/**
 * Creates the classifications of the test-{@link CoreferencePair}s by using the classifier
 * trained on the test-{@link CoreferencePair}s.
 * /*from   www  .  j  ava 2  s  . co m*/
 * @param testCorefs {@link CoreferencePair}s extraced from the test corpus by the ACR-Systems.
 * @return {@link CoreferencePair} which are predicted by our classifier to be correct.
 */
private List<CoreferencePair> createPrediction(Map<String, List<CoreferencePair>> testCorefs) throws Exception {
    List<CoreferencePair> predictions = new ArrayList<CoreferencePair>();
    for (String s : testCorefs.keySet()) {
        for (final CoreferencePair cp : testCorefs.get(s)) {
            Instance ini = ic.addCorefInstance(cp, s);
            ini.setDataset(ic.getInstances());

            /* use the classifier to select a label */
            if (wr.labelUnknownInstance(ini) == 0.0) {
                cp.setAcrSystem(ini.stringValue(ini.numAttributes() - 2));
                predictions.add(cp);
            }
        }
    }
    predictions = removeDuplicates(predictions);
    return predictions;
}

From source file:dkpro.similarity.experiments.sts2013.filter.LogFilter.java

License:Open Source License

@Override
protected Instance process(Instance inst) throws Exception {
    Instance newInst = new DenseInstance(inst.numAttributes());

    newInst.setValue(0, inst.value(0));/*from w  w  w . j  a  va  2s .c o m*/

    for (int i = 1; i < inst.numAttributes() - 1; i++) {
        double newVal = Math.log(inst.value(i) + 1);
        newInst.setValue(i, newVal);
    }

    newInst.setValue(inst.numAttributes() - 1, inst.value(inst.numAttributes() - 1));

    return newInst;
}

From source file:edu.drexel.psal.jstylo.verifiers.WLSVM.java

License:Open Source License

/**
 * Converts an ARFF Instance into a string in the sparse format accepted by
 * LIBSVM//  w  ww.  j  ava2s.  co  m
 * 
 * @param instance
 * @return
 */
protected String InstanceToSparse(Instance instance) {
    String line = new String();
    int c = (int) instance.classValue();
    if (c == 0)
        c = -1;
    line = c + " ";
    for (int j = 1; j < instance.numAttributes(); j++) {
        if (j - 1 == instance.classIndex()) {
            continue;
        }
        if (instance.isMissing(j - 1))
            continue;
        if (instance.value(j - 1) != 0)
            line += " " + j + ":" + instance.value(j - 1);
    }
    // LOG.info(line); 
    return (line + "\n");
}

From source file:edu.oregonstate.eecs.mcplan.abstraction.WekaUtil.java

License:Open Source License

public static double[] unlabeledFeatures(final Instance i) {
    assert (i.dataset() != null);
    assert (i.dataset().classIndex() == i.numAttributes() - 1);
    final double[] phi = new double[i.numAttributes() - 1];
    for (int j = 0; j < i.numAttributes() - 1; ++j) {
        phi[j] = i.value(j);//from  ww  w . j a va  2 s .c o  m
    }
    return phi;
}

From source file:edu.oregonstate.eecs.mcplan.ml.WekaGlue.java

License:Open Source License

public static RealVector toRealVector(final Instance inst) {
    final RealVector v = new ArrayRealVector(inst.numAttributes());
    for (int i = 0; i < inst.numAttributes(); ++i) {
        v.setEntry(i, inst.value(i));/* w  w w.j a  va  2s . c  o  m*/
    }
    return v;
}