Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/99617
Title: X2R: a fast rule generator
Authors: Liu, Huan 
Tan, Sun Teck 
Issue Date: 1995
Citation: Liu, Huan,Tan, Sun Teck (1995). X2R: a fast rule generator. Proceedings of the IEEE International Conference on Systems, Man and Cybernetics 2 : 1631-1635. ScholarBank@NUS Repository.
Abstract: Although they can learn from raw data, many concept learning algorithms require that the training data contain only discrete data. However, real world problems contain, more often than not, both numeric and discrete data. So before these algorithms can be applied, data discretization (quantization) is needed. This paper introduces X2R, a simple and fast algorithm that can be applied to both numeric and discrete data, and generate rules from datasets like Season-Classification, Golf-Playing that contain continuous and/or discrete data. The empirical results demonstrate that X2R can effectively generate rules from the raw data and perform better than some of its peers in terms of the quality of rules and time complexities.
Source Title: Proceedings of the IEEE International Conference on Systems, Man and Cybernetics
URI: http://scholarbank.nus.edu.sg/handle/10635/99617
ISSN: 08843627
Appears in Collections:Staff Publications

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