setInputFormat(getInputFormat());
setInputFormat(getInputFormat());
Normalize norm = new Normalize(); norm.setInputFormat(train); train = Filter.useFilter(train, norm); RemoveUseless ru = new RemoveUseless(); ru.setInputFormat(train); train = Filter.useFilter(train, ru); Ranker rank = new Ranker(); InfoGainAttributeEval eval = new InfoGainAttributeEval(); eval.buildEvaluator(train);
m_AttFilter.setInputFormat(train); train = Filter.useFilter(train, m_AttFilter);
m_AttFilter.setInputFormat(train); train = Filter.useFilter(train, m_AttFilter);
m_RemoveUseless.setInputFormat(m_data); m_data = Filter.useFilter(data, m_RemoveUseless);
m_removeUseless.setInputFormat(m_instances); m_instances = Filter.useFilter(m_instances, m_removeUseless);
m_removeUseless.setInputFormat(m_instances); m_instances = Filter.useFilter(m_instances, m_removeUseless);
m_RemoveUseless.setInputFormat(insts); insts = Filter.useFilter(insts, m_RemoveUseless); insts.deleteWithMissingClass();
m_RemoveUseless.setInputFormat(insts); insts = Filter.useFilter(insts, m_RemoveUseless); insts.deleteWithMissingClass();
m_RemoveUseless.setInputFormat(insts); insts = Filter.useFilter(insts, m_RemoveUseless); insts.deleteWithMissingClass();