Szczegóły publikacji
Opis bibliograficzny
Knowledge visualization using optimized general logic diagrams / Bartłomiej ŚNIEŻYŃSKI, Robert Szymacha, Ryszard S. Michalski // W: Intelligent Information Processing and Web Mining : proceedings of the international IIS: IIPWM '05 conference : Gdansk, Poland, June 13–16, 2005 / eds. Mieczysław A. Kłopotek, Sławomir T. Wierzchoń, Krzysztof Trojanowski. — Berlin ; Heidelberg ; New York : Springer-Verlag, 2005. — ( Advances in Soft Computing ; ISSN 1615-3871 ). — ISBN: 3-540-25056-5. — S. 137–145. — Bibliogr. s. 143, Abstr.
Autorzy (3)
- AGHŚnieżyński Bartłomiej
- AGHSzymacha Robert
- Michalski Ryszard S.
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 25486 |
|---|---|
| Data dodania do BaDAP | 2006-01-14 |
| DOI | 10.1007/3-540-32392-9_15 |
| Rok publikacji | 2005 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Czasopismo/seria | Advances in Soft Computing |
Abstract
Knowledge Visualizer (KV) uses a General Logic Diagram (GLD) to display examples and/or various forms of knowledge learned from them in a planar model of a multi-dimensional discrete space. Knowledge can be in different forms, for example, decision rules, decision trees, logical expressions, clusters, classifiers, and neural nets with discrete input variables. KV is implemented as a module of the inductive database system VINLEN, which integrates a conventional database system with a range of inductive inference and data mining capabilities. This paper describes briefly the KV module and then focuses on the problem of arranging attributes that span the diagram in a way that leads to the most readable rule visualization in the diagram. This problem has been solved by applying a simulated annealing.
