ART: A Hybrid Classification Model
作者:Fernando Berzal, Juan-Carlos Cubero, Daniel Sánchez, José María Serrano
摘要
This paper presents a new family of decision list induction algorithms based on ideas from the association rule mining context. ART, which stands for ‘Association Rule Tree’, builds decision lists that can be viewed as degenerate, polythetic decision trees. Our method is a generalized “Separate and Conquer” algorithm suitable for Data Mining applications because it makes use of efficient and scalable association rule mining techniques.
论文关键词:supervised learning, classification, decision lists, decision trees, association rules, Data Mining
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论文官网地址:https://doi.org/10.1023/B:MACH.0000008085.22487.a6