Robust Constructive Induction

Bernhard Pfahringer

Abstract: We describe how CiPF 2.0, a propositional constructive learner, can cope with both noise and representation mismatch in training examples simultaneously. CiPF 2.0 abilities stem from coupling the robust selective learner C4.5 with a sophisticated constructive induction component. An important new constructive operator incorporated into CiPF 2.0 is the simplified Kramer operator abstracting combinations of two attributes into a single new boolean attribute. The so-called Minimum Description Length (MDL) principle acts as a powerful control heuristic guiding search in the representation space through the abundance of opportunities for constructively adding new attributes. Claims are confirmed empirically by experiments in two artificial domains.