/**
* Classifies the given instance using the linear regression function.
*
* @param instance the test instance
* @return the classification
* @throws Exception if classification can't be done successfully
*/
public double classifyInstance(Instance instance) throws Exception {
// Filter instance
m_Missing.input(instance);
m_Missing.batchFinished();
instance = m_Missing.output();
if (!m_onlyNumeric && m_NominalToBinary != null) {
m_NominalToBinary.input(instance);
m_NominalToBinary.batchFinished();
instance = m_NominalToBinary.output();
}
if (m_Filter != null) {
m_Filter.input(instance);
m_Filter.batchFinished();
instance = m_Filter.output();
}
double result = m_optimizer.SVMOutput(instance);
return result * m_x1 + m_x0;
}
