Examples of weka.core.DenseInstance

weka.core.DenseInstance
te empty instance with three attribute values
Instance inst = new DenseInstance(3);

// Set instance's values for the attributes "length", "weight", and "position"
inst.setValue(length, 5.3);
inst.setValue(weight, 300);
inst.setValue(position, "first");

// Set instance's dataset to be the dataset "race"
inst.setDataset(race);

// Print the instance
System.out.println("The instance: " + inst);
...

All methods that change an instance's attribute values are safe, ie. a change of an instance's attribute values does not affect any other instances. All methods that change an instance's attribute values clone the attribute value vector before it is changed. If your application heavily modifies instance values, it may be faster to create a new instance from scratch. @author Eibe Frank (eibe@cs.waikato.ac.nz) @version $Revision: 5987 $

    String    field;


    result = new StringBuffer();
    
    if (inst instanceof SparseInstance) {
      outInst = new DenseInstance(inst.weight(), inst.toDoubleArray());
      outInst.setDataset(inst.dataset());
    }
    else {
      outInst = inst;
    }

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      }
       Instance inst;
       if (m_CreateSparseData)
   inst = new SparseInstance(1.0, vals);
       else
   inst = new DenseInstance(1.0, vals);
       //get rid of m_idColumn
       if(m_DataBaseConnection.getUpperCase())
              m_idColumn = m_idColumn.toUpperCase();
       if(m_structure.attribute(0).name().equals(m_idColumn)){
            inst.deleteAttributeAt(0);

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        vals[0] = current.value(10); // sample size
        vals[1] = (current.value(0) * tpCost
            + current.value(1) * fnCost
            + current.value(2) * fpCost
            + current.value(3) * tnCost) * scaleFactor;
        Instance newInst = new DenseInstance(1.0, vals);
        costBenefitI.add(newInst);
      }
      
      costBenefitI.compactify();

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      atts[i + 7] = random.nextInt(2);


    atts[atts.length - 1] = selected;


    // create instance
    result  = new DenseInstance(1.0, atts);
    result.setDataset(m_DatasetFormat);


    return result;
  }

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          else {
            values[i] = toPredict.value(i-1);
          }
        }


        m_PlotInstances.add(new DenseInstance(1.0, values));
        
        if (toPredict.classAttribute().isNominal()) {
          if (toPredict.isMissing(toPredict.classIndex()) || Utils.isMissingValue(pred)) {
            m_PlotShapes.addElement(new Integer(Plot2D.MISSING_SHAPE));
          }

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    values[m_PlotInstances.numAttributes() + n*3 + 1] = Utils.missingValue();
    values[m_PlotInstances.numAttributes() + n*3 + 2] = Utils.missingValue();
  }
      }
      // create new Instance
      newInst = new DenseInstance(inst.weight(), values);
      data.add(newInst);
    }
    
    m_PlotInstances = data;
  }

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      } else {
        m_vals[i] = Utils.missingValue();
      }
    }
    
    Instance newInst = new DenseInstance(incoming.weight(), m_vals);
    newInst.setDataset(m_modelHeader);


    return newInst;
  }

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    newInst[0] = (double) data.attribute(0).addStringValue(txtStr.toString());
    if (m_OutputFilename)
      newInst[1] = (double) data.attribute(1).addStringValue(subdirPath + File.separator + files[j]);
    newInst[data.classIndex()] = (double) k;
    data.add(new DenseInstance(1.0, newInst));
          is.close();
  }
  catch (Exception e) {
    System.err.println("failed to convert file: " + directoryPath + File.separator + subdirPath + File.separator + files[j]);
  }

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          newInst[1] = 0;
          structure.attribute(1).setStringValue(txt.getAbsolutePath());
        }
      }
      newInst[structure.classIndex()] = (double) m_lastClassDir;
      Instance inst = new DenseInstance(1.0, newInst);
      inst.setDataset(structure);
      is.close();
      
      m_lastClassDir++;
      if (m_lastClassDir == structure.classAttribute().numValues()) {
        m_lastClassDir = 0;

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      resetQueue();
      m_NewBatch = false;
    }
    Instance inst = null;
    if (instance instanceof SparseInstance) {
      inst = new DenseInstance(instance.weight(), instance.toDoubleArray());
      inst.setDataset(instance.dataset());
    } else {
      inst = instance;
    }
    push(inst);

View Full Code Here

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