Efficient incremental induction of decision trees

作者:Dimitrios Kalles, Tim Morris

摘要

This paper proposes a method to improve ID5R, an incremental TDIDT algorithm. The new method evaluates the quality of attributes selected at the nodes of a decision tree and estimates a minimum number of steps for which these attributes are guaranteed such a selection. This results in reducing overheads during incremental learning. The method is supported by theoretical analysis and experimental results.

论文关键词:Incremental algorithm, decision tree induction

论文评审过程:

论文官网地址:https://doi.org/10.1007/BF00058613