To find the optimal branching of a nominal attribute at a node in an L-ary decision tree, one is often forced to search over all possible L-ary partitions for the one that yields t...
Don Coppersmith, Se June Hong, Jonathan R. M. Hosk...
This paper extends previous work on skewing, an approach to problematic functions in decision tree induction. The previous algorithms were applicable only to functions of binary v...
The main task in decision tree construction algorithms is to find the "best partition" of the set of objects. In this paper, we investigate the problem of optimal binary ...
Abstract. In supervised learning, discretization of the continuous explanatory attributes enhances the accuracy of decision tree induction algorithms and naive Bayes classifier. M...
Decision trees are among the most popular pattern types in data mining due to their intuitive representation. However, little attention has been given on the definition of measure...