private void generateGaussianExamples(Instances format,int numInstances,Random random,SubspaceClusterDefinition cl,String cName){
  boolean makeInteger=cl.isInteger();
  Instance example=null;
  int numAtts=m_NumAttributes;
  if (getClassFlag()) {
    numAtts++;
  }
  example=new DenseInstance(numAtts);
  example.setDataset(format);
  boolean[] attributes=cl.getAttributes();
  double[] meanValue=cl.getMeanValue();
  double[] stddevValue=cl.getStddevValue();
  for (int j=0; j < numInstances; j++) {
    int num=-1;
    for (int i=0; i < m_NumAttributes; i++) {
      if (attributes[i]) {
        num++;
        double value=meanValue[num] + (random.nextGaussian() * stddevValue[num]);
        if (makeInteger) {
          value=Math.round(value);
        }
        example.setValue(i,value);
      }
 else {
        example.setMissing(i);
      }
    }
    if (getClassFlag()) {
      example.setClassValue(cName);
    }
    format.add(example);
  }
}

private void generateGaussianExamples ( Instances format , int numInstances , Random random , SubspaceClusterDefinition cl , String cName ) { boolean makeInteger = cl . isInteger ( ) ; Instance example = null ; int numAtts = m_NumAttributes ; if ( getClassFlag ( ) ) { numAtts ++ ; } example = new DenseInstance ( numAtts ) ; example . setDataset ( format ) ; boolean [ ] attributes = cl . getAttributes ( ) ; double [ ] meanValue = cl . getMeanValue ( ) ; double [ ] stddevValue = cl . getStddevValue ( ) ; for ( int j = 0 ; j < numInstances ; j ++ ) { int num = - 1 ; for ( int i = 0 ; i < m_NumAttributes ; i ++ ) { if ( attributes [ i ] ) { num ++ ; double value = meanValue [ num ] + ( random . nextGaussian ( ) * stddevValue [ num ] ) ; if ( makeInteger ) { value = Math . round ( value ) ; } example . setValue ( i , value ) ; } else { example . setMissing ( i ) ; } } if ( getClassFlag ( ) ) { example . setClassValue ( cName ) ; } format . add ( example ) ; } }
generate examples for a uniform cluster dataset .
