Robust Constructive Induction

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 (and its production rule generator) with a sophisticated constructive induction component. An important new general constructive operator incorporated into CiPF 2.0 is the simpliied 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 connrmed empirically by experiments in two artiicial domains.