Knowledge Visualization Using Optimized General Logic Diagrams

Autor:	Bartłomiej Śnieżyński, Ryszard S. Michalski, R. Szymacha
Rok vydání:	2006
Předmět:	Theoretical computer science Artificial neural network Computer science Discrete space Simulated annealing Diagram Decision tree Decision rule Data mining Inductive reasoning computer.software_genre computer Visualization
Zdroj:	Advances in Soft Computing ISBN: 3540250565 Intelligent Information Systems
DOI:	10.1007/3-540-32392-9_15
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::7a27fd3c6a9a095d2bc054863bd8a263 https://doi.org/10.1007/3-540-32392-9_15 Zobrazit plný text záznamu