@inproceedings{e089719337e44775bf916cd51ea9728c,
title = "A rough set and rule tree based incremental knowledge acquisition algorithm",
abstract = "As a special way of human brains in 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 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.",
author = "Zheng Zheng and Guoyin Wang and Yu Wu",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2003.; 9th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, RSFDGrC 2003 ; Conference date: 26-05-2003 Through 29-05-2003",
year = "2003",
doi = "10.1007/3-540-39205-x\_16",
language = "英语",
isbn = "3540140409",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "122--129",
editor = "Guoyin Wang and Qing Liu and Yiyu Yao and Andrzej Skowron",
booktitle = "Rough Sets, Fuzzy Sets, Data Mining and Granular Computing - 9th International Conference, RSFDGrC 2003, Proceedings",
address = "德国",
}