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Mathematical and Computational Applications is published by MDPI from Volume 21 Issue 1 (2016). Articles in this Issue were published by another publisher in Open Access under a CC-BY (or CC-BY-NC-ND) licence. Articles are hosted by MDPI on as a courtesy and upon agreement with the previous journal publisher.
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Math. Comput. Appl. 2005, 10(1), 113-120;

Pruning Decision Trees using Rules3 Inductive Learning Algorithm

King Saud University, College of Computer and Information Sciences, P.O.Box 51178, Riyadh, 11543, Saudi Arabia
Published: 1 April 2005
PDF [113 KB, uploaded 7 April 2016]


One important disadvantage of decision tree based inductive learning algorithms is that they use some irrelevant values to establish the decision tree. This causes the final rule set to be less general. To overcome with this problem the tree has to be pruned. In this article using the recently developed RULES inductive learning algorithm, pruning of a decision tree is explained. The decision tree is extracted for an example problem using the ID3 algorithm and then is pruned using RULES. The results obtained before and after pruning are compared. This shows that the pruned decision tree is more general.
Keywords: Pruning; Decision Trees; Inductive Learning Pruning; Decision Trees; Inductive Learning
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Aksoy, M.S. Pruning Decision Trees using Rules3 Inductive Learning Algorithm. Math. Comput. Appl. 2005, 10, 113-120.

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