Concept Formation by Incremental Conceptual Clustering
نویسندگان
چکیده
Incremental conceptual clustering is an important area of machine learning. It is concerned with summarizing data in a form of concept hierarchies, which will eventually ease the problem of knowledge acquisition for knowledge-based systems. In this paper we have described INC, a program that generates a hierarchy of concept descriptions incrementally. INC searches a space of classification hierarchies in both top-down and bottom-up fashion. The system was evaluated along four dimensions and tested in two domains: universities and countries.
منابع مشابه
Incremental Concept Formation Algorithms Based on Galois (Concept) Lattices
The Galois (or concept) lattice produced from a binary relation has been proved useful for many applications. Building the Galois lattice can be considered as a conceptual clustering method since it results in a concept hierarchy. This article presents incremental algorithms for updating the Galois lattice and corresponding graph, resulting in an incremental concept formation method. Different ...
متن کاملConstructive Induction by Incremental Concept Formation
This paper describes a framework that generates constructive induction schemes for the concept formation system COBWEB. The basis of this framework|context-dependent bias of multi-valued properties|provides a way for allowing COBWEB to deal with continuous and hierarchical property types as a special case of constructive induction. The constructive induction scheme does not introduce learning b...
متن کاملAn Incremental Concept Formation Approach to Learn and Discover from a Clinical Database
The main interest of this research is to discover clinical implications from a large PTCA (Percutaneous Transluminal Coronary Angioplasty) database. A case-based concept formation model D-UNIMEM, modified from Lebowitz's UNIMEM, is proposed for this purpose. In this model, we integrated two kinds of class membership and the index-conjunction class membership. The former is a polythetic clusteri...
متن کاملMining Data in Multi-perspectives
Knowledge discover in Data bases (KDD) concerns the development of models which allow the representation and organization of the knowledge hidden in data. Machine learning systems are an alternative to automate the KDD process. In particular, incremental concept formation systems construct hierarchical abstract representations from observations (non-classified description of specific entities, ...
متن کامل