Comparing Rapidminer decision tree and Weka's
Can someone please explain how Rapidminer decision tree operator is different from J48 (or W-J48) decision tree in Weka? The accuracy I get from the latter is considerably higher. Weka's documentation clearly mentioned that J48 is based on C4.5 algorithm. How about Rapidminer's? If they are the same why do they give different accuracies for similar parameters? Plus, despite Rapidminer's, Weka's cannot handle missing data point.