How to use

setInputFormat

method

in

weka.filters.unsupervised.attribute.Center

protected void fillCovariance() throws Exception {
 // just center the data or standardize it?
 if (m_center) {
  m_centerFilter = new Center();
  m_centerFilter.setInputFormat(m_TrainInstances);
  m_TrainInstances = Filter.useFilter(m_TrainInstances, m_centerFilter);
 } else {
  m_standardizeFilter = new Standardize();
  m_standardizeFilter.setInputFormat(m_TrainInstances);
  m_TrainInstances = Filter.useFilter(m_TrainInstances, m_standardizeFilter);
 }
 // now compute the covariance matrix
 m_Correlation = new UpperSymmDenseMatrix(m_NumAttribs);
 for (int i = 0; i < m_NumAttribs; i++) {
  for (int j = i; j < m_NumAttribs; j++) {
   double cov = 0;
   for (Instance inst: m_TrainInstances) {
    cov += inst.value(i) * inst.value(j);
   }
   cov /= m_TrainInstances.numInstances() - 1;
   m_Correlation.set(i, j, cov);
  }
 }
}

protected void fillCovariance() throws Exception {
 // just center the data or standardize it?
 if (m_center) {
  m_centerFilter = new Center();
  m_centerFilter.setInputFormat(m_TrainInstances);
  m_TrainInstances = Filter.useFilter(m_TrainInstances, m_centerFilter);
 } else {
  m_standardizeFilter = new Standardize();
  m_standardizeFilter.setInputFormat(m_TrainInstances);
  m_TrainInstances = Filter.useFilter(m_TrainInstances, m_standardizeFilter);
 }
 // now compute the covariance matrix
 m_Correlation = new UpperSymmDenseMatrix(m_NumAttribs);
 for (int i = 0; i < m_NumAttribs; i++) {
  for (int j = i; j < m_NumAttribs; j++) {
   double cov = 0;
   for (Instance inst: m_TrainInstances) {
    cov += inst.value(i) * inst.value(j);
   }
   cov /= m_TrainInstances.numInstances() - 1;
   m_Correlation.set(i, j, cov);
  }
 }
}

 m_centerFilter.setInputFormat(m_trainInstances);
 m_trainInstances = Filter.useFilter(m_trainInstances, m_centerFilter);
} else {

 m_centerFilter.setInputFormat(m_trainInstances);
 m_trainInstances = Filter.useFilter(m_trainInstances, m_centerFilter);
} else {