Meningitis data mining by cooperatively using GDT-RS and RSBR. This paper describes an application of two rough sets based systems, namely Generalized Distribution Table and Rough Set (GDT-RS) and Rough Sets with Boolean Reasoning (RSBR) respectively, for mining if-then rules in a meningitis dataset. GDT-RS is a soft hybrid induction system, and RSBR is used for discretization of real valued attributes as a pre-processing step realized before the GDT-RS starts. We argue that discretization of continuous valued attributes is an important pre-processing step in the rule discovery process. We illustrate the quality of rules discovered by GDT-RS is strongly affected by the result of discretization.

References in zbMATH (referenced in 19 articles , 1 standard article )

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  1. Luo, Sheng; Miao, Duoqian; Zhang, Zhifei; Zhang, Yuanjian; Hu, Shengdan: A neighborhood rough set model with nominal metric embedding (2020)
  2. Borowik, Grzegorz: Optimization on the complementation procedure towards efficient implementation of the index generation function (2019)
  3. Liu, Yaya; Qin, Keyun; Rao, Chang; Mahamadu, Mahamuda Alhaji: Object-parameter approaches to predicting unknown data in an incomplete fuzzy soft set (2017)
  4. Colomo-Palacios, Ricardo; González-Carrasco, Israel; López-Cuadrado, José Luis; García-Crespo, Ángel: ReSySTER: a hybrid recommender system for scrum team roles based on fuzzy and rough sets (2012)
  5. Qin, Hongwu; Ma, Xiuqin; Herawan, Tutut; Zain, Jasni Mohamad: DFIS: a novel data filling approach for an incomplete soft set (2012)
  6. Bodjanova, Slavka; Kalina, Martin: Gradual evaluation of granules of a fuzzy relation: R-related sets (2010)
  7. Sikora, Marek: Decision rule-based data models using TRS and NetTRS -- methods and algorithms (2010) ioport
  8. Al-Qaheri, Hameed; Hassanien, Aboul Ella; Abraham, Ajith: A generic scheme for generating prediction rules using rough sets (2009)
  9. Yang, Yong; Wang, Guoyin; Kong, Hao: Self-learning facial emotional feature selection based on rough set theory (2009)
  10. Yao, Yiyu: Probabilistic rough set approximations (2008)
  11. Pawlak, Zdzisław; Skowron, Andrzej: Rudiments of rough sets (2007)
  12. Sikora, Marek: Rule quality measures in creation and reduction of data rule models (2006)
  13. Zhong, Ning; Dong, Ju-Zhen; Ohsuga, Setsuo: Meningitis data mining by cooperatively using GDT-RS and RSBR. (2003)
  14. Miyahara, Tetsuhiro; Suzuki, Yusuke; Shoudai, Takayoshi; Uchida, Tomoyuki; Takahashi, Kenichi; Ueda, Hiroaki: Discovery of frequent tag tree patterns in semistructured web documents (2002)
  15. Zhong, Ning; Dong, Juzhen: Mining interesting rules in meningitis data by cooperatively using GDT-RS and RSBR (2002)
  16. Zhong, Ning; Dong, Ju-Zhen; Yao, Y. Y.; Ohsuga, Setsuo: Gastric cancer data mining with ordered information (2002)
  17. Zhong, Ning; Matsunaga, Takahisa; Liu, Chunnian: A text mining agents based architecture for personal e-mail filtering and management (2002)
  18. Zhong, Ning; Dong, Ju-Zhen; Ohsuga, Setsuo: Meningitis data mining by cooperatively using GDT-RS and RSBR (2001)
  19. Zhong, Ning; Skowron, Andrzej: A rough set-based knowledge discovery process (2001)