RRIA: A rough set and rule tree based incremental knowledge acquisition algorithm. As a special way in which the human brain is learning new knowledge, incremental learning is an important topic in AI. It is an object of many AI researchers to find an algorithm that can learn new knowledge quickly, based on original knowledge learned before, and in such way that the knowledge it acquires is efficient in real use. In this paper, we develop a rough set and rule tree based incremental knowledge acquisition algorithm. It can learn from a domain data set incrementally. Our simulation results show that our algorithm can learn more quickly than classical rough set based knowledge acquisition algorithms, and the performance of knowledge learned by our algorithm can be the same as or even better than classical rough set based knowledge acquisition algorithms. Besides, the simulation results also show that our algorithm outperforms ID4 in many aspects.

References in zbMATH (referenced in 16 articles , 1 standard article )

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  1. Liu, Ye; Zheng, Lidi; Xiu, Yeliang; Yin, Hong; Zhao, Suyun; Wang, Xizhao; Chen, Hong; Li, Cuiping: Discernibility matrix based incremental feature selection on fused decision tables (2020)
  2. Wenjun, Liu: An incremental approach to obtaining attribute reduction for dynamic decision systems (2016)
  3. Zhang, Qinghua; Zhang, Qiang; Wang, Guoyin: The uncertainty of probabilistic rough sets in multi-granulation spaces (2016)
  4. Li, Shaoyong; Li, Tianrui: Incremental update of approximations in dominance-based rough sets approach under the variation of attribute values (2015)
  5. Liu, Dun; Li, Tianrui; Zhang, Junbo: A rough set-based incremental approach for learning knowledge in dynamic incomplete information systems (2014)
  6. Shu, Wenhao; Shen, Hong: Updating attribute reduction in incomplete decision systems with the variation of attribute set (2014)
  7. Zhang, Junbo; Li, Tianrui; Chen, Hongmei: Composite rough sets for dynamic data mining (2014)
  8. Liu, Dun; Li, Tianrui; Ruan, Da; Zhang, Junbo: Incremental learning optimization on knowledge discovery in dynamic business intelligent systems (2011)
  9. Zhang, Guang-Quan; Zheng, Zheng; Lu, Jie; He, Qing: An algorithm for solving rule sets-based bilevel decision problems (2011)
  10. Zhang, Junbo; Li, Tianrui; Ruan, Da: Rough sets based incremental rule acquisition in set-valued information systems (2011)
  11. Chen, Hongmei; Li, Tianrui; Qiao, Shaojie; Ruan, Da: A rough set based dynamic maintenance approach for approximations in coarsening and refining attribute values (2010)
  12. Liu, Dun; Li, Tianrui; Ruan, Da; Zou, Weili: An incremental approach for inducing knowledge from dynamic information systems (2009)
  13. Wang, Guoyin; Zhang, Qinghua; Huang, Houkuan; Ye, Dongyi; Hu, Qinghua; Hu, Xuegang; Shi, Zhongzhi; Li, Yongli; Shang, Lin; An, Liping; Sai, Ying; Chen, Shanben; Liang, Jiye; Qin, Keyun; Zeng, Huanglin; Xie, Keming; Miao, Duoqian; Min, Fan; Wu, Zhaocong; Wu, Weizhi; Dai, Jianhua: Research on rough set theory and applications in China (2008)
  14. Pawlak, Zdzisław; Skowron, Andrzej: Rudiments of rough sets (2007)
  15. Hu, Feng; Wang, Guoyin; Huang, Hai; Wu, Yu: Incremental attribute reduction based on elementary sets (2005)
  16. Zheng, Zheng; Wang, Guoyin: RRIA: A rough set and rule tree based incremental knowledge acquisition algorithm (2004)