Mark Last

Most classification algorithms are aimed at predicting the value or values of a single target (class) attribute. However, some real-world classification tasks involve several targets that need to be predicted simultaneously. The Multiobjective Info-Fuzzy Network (M-IFN) algorithm builds an ordered (oblivious) decision-tree model for a multi-target classification task. After summarizing the principles and the properties of the M-IFN algorithm, this paper reviews three case studies of applying M-IFN to practical problems in industry and science.