Normalize norm = new Normalize(); norm.setInputFormat(train); Instances processed_train = Filter.useFilter(train, norm);
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);
setInputFormat(getInputFormat());
setInputFormat(getInputFormat());
m_Normalize.setInputFormat(m_data); m_data = Filter.useFilter(m_data, m_Normalize);
m_normalize.setInputFormat(data); data = Filter.useFilter(data, m_normalize);
m_normalize.setInputFormat(data); data = Filter.useFilter(data, m_normalize);
m_normalize.setInputFormat(data); data = Filter.useFilter(data, m_normalize);