Knowledge Visualization Using Optimized General Logic Diagrams
| dc.contributor.author | Śnieżyński, Bartłomiej | |
| dc.contributor.author | Szymacha, Robert | |
| dc.contributor.author | Michalski, Ryszard S. | |
| dc.date.accessioned | 2006-11-03T18:17:31Z | |
| dc.date.available | 2006-11-03T18:17:31Z | |
| dc.date.issued | 2005-06 | |
| dc.description.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. | |
| dc.format.extent | 2148 bytes | |
| dc.format.extent | 1523293 bytes | |
| dc.format.mimetype | text/xml | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.citation | Śnieżyński, B., Szymacha, R. and Michalski, R. S., "Knowledge Visualization Using Optimized General Logic Diagrams," Proceedings of the Intelligent Information Processing and Web Mining Conference, IIPWM 05, Gdansk, Poland, June 13-16, 2005. | |
| dc.identifier.uri | https://hdl.handle.net/1920/1492 | |
| dc.language.iso | en_US | |
| dc.relation.ispartofseries | P 05-3 | |
| dc.subject | Knowledge visualization | |
| dc.subject | General logic diagrams (GLD) | |
| dc.subject | Diagram optimization | |
| dc.subject | Machine learning | |
| dc.title | Knowledge Visualization Using Optimized General Logic Diagrams | |
| dc.type | Presentation |
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