Example usage for weka.core Instance setValue

List of usage examples for weka.core Instance setValue

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Introduction

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

Prototype

public void setValue(Attribute att, String value);

Source Link

Document

Sets a value of an nominal or string attribute to the given value.

Usage

From source file:meka.classifiers.multilabel.meta.MBR.java

License:Open Source License

@Override
public double[] distributionForInstance(Instance instance) throws Exception {

    int c = instance.classIndex();

    double result[] = m_BASE.distributionForInstance(instance);

    instance.setDataset(null);/*from   ww  w .  j  av  a2  s  . com*/

    for (int i = 0; i < c; i++) {
        instance.insertAttributeAt(c);
    }

    instance.setDataset(m_InstancesTemplate);

    for (int i = 0; i < c; i++) {
        instance.setValue(c + i, result[i]);
    }

    return m_META.distributionForInstance(instance);
}

From source file:meka.core.CCUtils.java

License:Open Source License

/**
 * SetPath - set 'path[]' into the first L attributes of Instance 'xy'.
 * @param   xy      an Example (x,y)//from   ww  w .  j ava2  s  .  co m
 * @param   path   a label vector
 */
public static void setPath(Instance xy, double path[]) {
    int L = xy.classIndex(); // = path.length
    for (int j = 0; j < L; j++) {
        xy.setValue(j, (int) Math.round(path[j])); // x = x + path_j
    }
}

From source file:meka.core.Metrics.java

License:Open Source License

/** Get Data for Plotting PR and ROC curves. */
public static Instances curveDataMacroAveraged(int Y[][], double P[][]) {

    // Note: 'Threshold' contains the probability threshold that gives rise to the previous performance values.

    Instances curveData[] = curveData(Y, P);

    int L = curveData.length;

    int noNullIndex = -1;

    for (int i = 0; i < curveData.length; i++) {
        if (curveData[i] == null) {
            L--;// w w w.  j  a v  a2s  .  com
        } else {
            if (noNullIndex == -1) {
                // checking for the first curveData that is not null (=does not consist of
                // only missing values or 0s)
                noNullIndex = i;
            }

        }

    }

    Instances avgCurve = new Instances(curveData[noNullIndex], 0);
    int D = avgCurve.numAttributes();

    for (double t = 0.0; t < 1.; t += 0.01) {
        Instance x = (Instance) curveData[noNullIndex].instance(0).copy();
        //System.out.println("x1\n"+x);
        boolean firstloop = true;
        for (int j = 0; j < L; j++) {

            // if there are only missing values in a column, curveData[j] is null

            if (curveData[j] == null) {
                continue;
            }

            int i = ThresholdCurve.getThresholdInstance(curveData[j], t);
            if (firstloop) {
                // reset
                for (int a = 0; a < D; a++) {
                    x.setValue(a, curveData[j].instance(i).value(a) * 1. / L);
                }
                firstloop = false;
            } else {
                // add
                for (int a = 0; a < D; a++) {
                    double v = x.value(a);
                    x.setValue(a, v + curveData[j].instance(i).value(a) * 1. / L);
                }
            }
        }
        //System.out.println("x2\n"+x);
        avgCurve.add(x);
    }

    /*
      System.out.println(avgCurve);
      System.exit(1);
            
      // Average everything
      for (int i = 0; i < avgCurve.numInstances(); i++) {
      for(int j = 0; j < L; j++) {
      for (int a = 0; a < D; a++) {
      double o = avgCurve.instance(i).value(a);
      avgCurve.instance(i).setValue(a, o / L);
      }
      }
      }
    */
    return avgCurve;
}

From source file:meka.core.MLUtils.java

License:Open Source License

/**
 * CopyValues - Set x_dest[j+offset] = x_src[i+from].
 *///  w w  w.  jav  a  2s .c  o m
public static final Instance copyValues(Instance x_dest, Instance x_src, int from, int offset) {
    int d = x_src.numAttributes();
    for (int i = from, j = 0; i < d; i++, j++) {
        x_dest.setValue(j + offset, x_src.value(i));
    }
    return x_dest;
}

From source file:meka.core.MLUtils.java

License:Open Source License

/**
 * CopyValues - Set x_dest[i++] = x_src[j] for all j in indices[].
 *//*from   w  ww  .java2 s .c  o  m*/
public static final Instance copyValues(Instance x_dest, Instance x_src, int indices[]) {
    int i = 0;
    for (int j : indices) {
        x_dest.setValue(i++, x_src.value(j));
    }
    return x_dest;
}

From source file:meka.core.MLUtils.java

License:Open Source License

/**
 * SetValues - set the attribute values in Instsance x (having L labels) to z[].
 * TODO: call above method/*w  ww  . j  a va2  s.co  m*/
 */
public static final Instance setValues(Instance x, double z[], int L) {
    for (int a = 0; a < z.length; a++) {
        x.setValue(L + a, z[a]);
    }
    return x;
}

From source file:meka.core.MLUtils.java

License:Open Source License

/** Clear Labels -- set the value of all label attributes to 0.0 */
public static void clearLabels(Instance x) {
    int L = x.classIndex();
    for (int j = 0; j < L; j++)
        x.setValue(j, 0.0);
}

From source file:meka.core.Result.java

License:Open Source License

/**
 * Convert a list of Results into an Instances.
 * @param results An ArrayList of Results
 * @return   Instances/*  w w  w .j  av  a2  s.c  o  m*/
 */
public static Instances getResultsAsInstances(ArrayList<HashMap<String, Object>> metrics) {

    HashMap<String, Object> o_master = metrics.get(0);
    ArrayList<Attribute> attInfo = new ArrayList<Attribute>();
    for (String key : o_master.keySet()) {
        if (o_master.get(key) instanceof Double) {
            //System.out.println("key="+key);
            attInfo.add(new Attribute(key));
        }
    }

    Instances resultInstances = new Instances("Results", attInfo, metrics.size());

    for (HashMap<String, Object> o : metrics) {
        Instance rx = new DenseInstance(attInfo.size());
        for (Attribute att : attInfo) {
            String name = att.name();
            rx.setValue(att, (double) o.get(name));
        }
        resultInstances.add(rx);
    }

    //System.out.println(""+resultInstances);
    return resultInstances;

}

From source file:meka.core.SuperLabelUtils.java

License:Open Source License

/**
 * Super Label Transformation - transform dataset D into a dataset with <code>k</code> multi-class target attributes.
 * Use the NSR/PS-style pruning and recomposition, according to partition 'indices', and pruning values 'p' and 'n'.
 * @see PSUtils.PSTransformation// w  ww  .  java2 s.c  o m
 * @param indices   m by k: m super variables, each relating to k original variables
 * @param    D   either multi-label or multi-target dataset
 * @param    p   pruning value
 * @param    n   subset relpacement value
 * @return       a multi-target dataset
 */
public static Instances SLTransformation(Instances D, int indices[][], int p, int n) {

    int L = D.classIndex();
    int K = indices.length;
    ArrayList<String> values[] = new ArrayList[K];
    HashMap<String, Integer> counts[] = new HashMap[K];

    // create D_
    Instances D_ = new Instances(D);

    // clear D_
    // F.removeLabels(D_,L);
    for (int j = 0; j < L; j++) {
        D_.deleteAttributeAt(0);
    }

    // create atts
    for (int j = 0; j < K; j++) {
        int att[] = indices[j];
        //int values[] = new int[2]; //getValues(indices,D,p);
        counts[j] = getCounts(D, att, p);
        Set<String> vals = counts[j].keySet(); //getValues(D,att,p);
        values[j] = new ArrayList(vals);
        D_.insertAttributeAt(new Attribute(encodeClass(att), new ArrayList(vals)), j);
    }

    // copy over values
    ArrayList<Integer> deleteList = new ArrayList<Integer>();
    for (int i = 0; i < D.numInstances(); i++) {
        Instance x = D.instance(i);
        for (int j = 0; j < K; j++) {
            String y = encodeValue(x, indices[j]);
            try {
                D_.instance(i).setValue(j, y); // y =
            } catch (Exception e) {
                // value not allowed
                deleteList.add(i); // mark it for deletion
                String y_close[] = getTopNSubsets(y, counts[j], n); // get N subsets
                for (int m = 0; m < y_close.length; m++) {
                    //System.out.println("add "+y_close[m]+" "+counts[j]);
                    Instance x_copy = (Instance) D_.instance(i).copy();
                    x_copy.setValue(j, y_close[m]);
                    x_copy.setWeight(1.0 / y_close.length);
                    D_.add(x_copy);
                }
            }
        }
    }
    // clean up
    Collections.sort(deleteList, Collections.reverseOrder());
    //System.out.println("Deleting "+deleteList.size()+" defunct instances.");
    for (int i : deleteList) {
        D_.delete(i);
    }
    // set class
    D_.setClassIndex(K);
    // done!
    return D_;
}

From source file:meka.filters.multilabel.SuperNodeFilter.java

License:Open Source License

/**
 * Merge Labels - Make a new 'D', with labels made into superlabels, according to partition 'indices', and pruning values 'p' and 'n'.
 * @param    D   assume attributes in D labeled by original index
 * @return       Instances with attributes at j and k moved to position L as (j,k), with classIndex = L-1
 *///from  w  w  w. j a v a 2s .  c om
public static Instances mergeLabels(Instances D, int indices[][], int p, int n) {

    int L = D.classIndex();
    int K = indices.length;
    ArrayList<String> values[] = new ArrayList[K];
    HashMap<String, Integer> counts[] = new HashMap[K];

    // create D_
    Instances D_ = new Instances(D);

    // clear D_
    for (int j = 0; j < L; j++) {
        D_.deleteAttributeAt(0);
    }

    // create atts
    for (int j = 0; j < K; j++) {
        int att[] = indices[j];
        //int values[] = new int[2]; //getValues(indices,D,p);
        counts[j] = getCounts(D, att, p);
        Set<String> vals = counts[j].keySet(); //getValues(D,att,p);
        values[j] = new ArrayList(vals);
        D_.insertAttributeAt(new Attribute(encodeClass(att), new ArrayList(vals)), j);
    }

    // copy over values
    ArrayList<Integer> deleteList = new ArrayList<Integer>();
    for (int i = 0; i < D.numInstances(); i++) {
        Instance x = D.instance(i);
        for (int j = 0; j < K; j++) {
            String y = encodeValue(x, indices[j]);
            try {
                D_.instance(i).setValue(j, y); // y = 
            } catch (Exception e) {
                // value not allowed
                deleteList.add(i); // mark it for deletion
                String y_close[] = NSR.getTopNSubsets(y, counts[j], n); // get N subsets
                for (int m = 0; m < y_close.length; m++) {
                    //System.out.println("add "+y_close[m]+" "+counts[j]);
                    Instance x_copy = (Instance) D_.instance(i).copy();
                    x_copy.setValue(j, y_close[m]);
                    x_copy.setWeight(1.0 / y_close.length);
                    D_.add(x_copy);
                }
            }
        }
    }
    // clean up
    Collections.sort(deleteList, Collections.reverseOrder());
    //System.out.println("Deleting "+deleteList.size()+" defunct instances.");
    for (int i : deleteList) {
        D_.delete(i);
    }
    // set class
    D_.setClassIndex(K);
    // done!
    D = null;
    return D_;
}