Study on Comparison of Discretization Methods

Authors:
Liu Peng;Wang Qing;Gu Yujia
Affiliations:
-;-;-
Venue:
AICI '09 Proceedings of the 2009 International Conference on Artificial Intelligence and Computational Intelligence - Volume 04
Year:
2009

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Abstract

Discrete features play an important role in data mining. How to best discretize continuous features has always been a NP-hard problem. This paper introduces diverse taxonomies in the existing literature to classify discretization methods, as well as idea and drawbacks of some typical methods. Furthermore, a comparison of these methods is studied. It's essential to select proper methods depending on learning environment. At last, the thought of choosing the best discretization methods in association analysis is proposed as future research.