Adaptive Non-Deterministic Decision Trees: General Formulation and Case Study
Main Article Content
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.
Article Details
How to Cite
Pistori, H., Neto, J. J., & Pereira, M. C. (2006). Adaptive Non-Deterministic Decision Trees: General Formulation and Case Study. INFOCOMP Journal of Computer Science, 5(1), 35–40. Retrieved from https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/120
Section
Articles
Upon receipt of accepted manuscripts, authors will be invited to complete a copyright license to publish the paper. At least the corresponding author must send the copyright form signed for publication. It is a condition of publication that authors grant an exclusive licence to the the INFOCOMP Journal of Computer Science. This ensures that requests from third parties to reproduce articles are handled efficiently and consistently and will also allow the article to be as widely disseminated as possible. In assigning the copyright license, authors may use their own material in other publications and ensure that the INFOCOMP Journal of Computer Science is acknowledged as the original publication place.