/** * 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; }