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Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/10204

Title: Adaptive non-deterministic decision trees: general formulation and case study
???metadata.dc.creator???: Pistori, Hemerson
José Neto, João
Pereira, Mauro Conti
Keywords: Rule-driven adaptive devices
Machine learning
Decision trees
Dispositivo adaptativo dirigido por regras
Aprendizagem automática
Árvore de decisão
Publisher: Editora da UFLA
???metadata.dc.date???: 1-Mar-2006
Citation: PISTORI, H.; JOSÉ NETO, J.; PEREIRA, M. C. Adaptive non-deterministic decision trees: general formulation and case study. INFOCOMP: Journal of Computer Science, Lavras, v. 5, n. 1, p. 35-40, Mar. 2006.
Abstract: This paper introduces the adaptive non-deterministic decision tree, a formal device derived from adaptive device theory. ANDD-tree is a new framework for the development of supervised learning techniques. The general formulation of this framework, a case study and some experimental results are also presented.
Other Identifiers: http://www.dcc.ufla.br/infocomp/index.php/INFOCOMP/article/view/120
???metadata.dc.language???: eng
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