Examples of weka.core.SparseInstance

weka.core.SparseInstance
Class for storing an instance as a sparse vector. A sparse instance only requires storage for those attribute values that are non-zero. Since the objective is to reduce storage requirements for datasets with large numbers of default values, this also includes nominal attributes -- the first nominal value (i.e. that which has index 0) will not require explicit storage, so rearrange your nominal attribute value orderings if necessary. Missing values will be stored explicitly. @author Eibe Frank @version $Revision: 5970 $

    vals[i - 1] = Instance.missingValue();
  }
      }
      Instance newInst;
      if (m_CreateSparseData) {
  newInst = new SparseInstance(1.0, vals);
      } else {
  newInst = new Instance(1.0, vals);
      }
      instances.addElement(newInst);
      rowCount++;

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  break;
    }


    // create instance
    if (instance instanceof SparseInstance)
      result = new SparseInstance(instance.weight(), newVals);
    else
      result = new Instance(instance.weight(), newVals);
    
    return result;
  }

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    }
    if (m_NewBatch) {
      resetQueue();
      m_NewBatch = false;
    }
    Instance inst = new SparseInstance(instance);
    inst.setDataset(instance.dataset());
    push(inst);
    return true;
  }

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      Double value = (Double)contained.get(index);
      values[i] = value.doubleValue();
      indices[i] = index.intValue();
    }


    Instance inst = new SparseInstance(instance.weight(), values, indices, 
  outputFormatPeek().numAttributes());
    inst.setDataset(outputFormatPeek());


    v.addElement(inst);


    return firstCopy;    
  }

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      instanceVals[instance.numAttributes()] = Instance.missingValue();
    }


    // create new instance
    if (original instanceof SparseInstance) {
      processed = new SparseInstance(original.weight(), instanceVals);
    } else {
      processed = new Instance(original.weight(), instanceVals);
    }


    processed.setDataset(instance.dataset());

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      int current = m_SelectedAttributes[i];
      vals[i] = instance.value(current);
    }
    Instance inst = null;
    if (instance instanceof SparseInstance)
      inst = new SparseInstance(instance.weight(), vals);
    else
      inst = new Instance(instance.weight(), vals);


    inst.setDataset(getOutputFormat());
    copyValues(inst, false, instance.dataset(), getOutputFormat());

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    m_attributeExpression.evaluateExpression(vals);


    Instance inst = null;
    if (instance instanceof SparseInstance) {
      inst = new SparseInstance(instance.weight(), vals);
    } else {
      inst = new Instance(instance.weight(), vals);
    }


    inst.setDataset(getOutputFormat());

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        vals[i] = dest.value(i);
      }
    }
    Instance inst = null;
    if (dest instanceof SparseInstance) {
      inst = new SparseInstance(dest.weight(), vals);
    } else {
      inst = new Instance(dest.weight(), vals);
    }
    inst.setDataset(dest.dataset());
    return inst;

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    indices[num] = instance.index(j);
    num++;
  }
      } 
      if (num == instance.numValues()) {
  inst = new SparseInstance(instance.weight(), vals, indices,
                                  instance.numAttributes());
      } else {
  double []tempVals = new double[num];
  int []tempInd = new int[num];
  System.arraycopy(vals, 0, tempVals, 0, num);
  System.arraycopy(indices, 0, tempInd, 0, num);
  inst = new SparseInstance(instance.weight(), tempVals, tempInd,
                                  instance.numAttributes());
      }
    } else {
      double []vals = new double[getInputFormat().numAttributes()];
      for (int j = 0; j < instance.numAttributes(); j++) {

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      }  
      double[] tempVals = new double[ind];
      int[] tempInd = new int[ind];
      System.arraycopy(newVals, 0, tempVals, 0, ind);
      System.arraycopy(newIndices, 0, tempInd, 0, ind);
      inst = new SparseInstance(instance.weight(), tempVals, tempInd,
                                instance.numAttributes());
    } 
    else {
      double[] vals = instance.toDoubleArray();
      for (int j = 0; j < getInputFormat().numAttributes(); j++) {

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