LEARNING TO PREDICT - INC2.5

This paper discusses INC2.5, an incremental concept formation system. The goal of INC2.5 is to form a hierarchy of concept descriptions base d on previously seen instances which will be used to predict the class ification of a new instance description. Each subtree of the hierarchy consists of instances which are similar to each other. The further fr om the root, the greater the similarity is between the instances withi n the same groupings. The ability to classify instances based on their description has many applications. For example, in the medical field doctors are required daily to diagnose patients; in other words, class ify patients according to their symptoms. INC2.5 has been successfully applied to several domains, including breast cancer, general trauma, congressional voting records, and the monk's problems.