DocumentCode
424197
Title
Incremental machine learning theorem and algorithm based on DSM method
Author
Zhou, Jian-Guo ; Xia, De-Lin ; Pu, Liu-Yan ; Wu, Jing ; Jiang, Hao
Author_Institution
Sch. of Electron. Inf., Wuhan Univ., Hubei, China
Volume
4
fYear
2004
fDate
26-29 Aug. 2004
Firstpage
2202
Abstract
An incremental and efficient algorithm is the key to knowledge acquisition and machine learning. The DSM is defined in the paper, the important principle of the best knowledge reduction is found and a new method is put forward through analyzing the elements mud & mus in DSM. The reduction efficiency is improved and the reduced rules are the least and the number of the attributes in the rules is the least too, so it is the best knowledge reduction. We also put forward a new incremental learning method based on DSM. The method can automatically maintain the rules when the new instances are added.
Keywords
knowledge engineering; learning (artificial intelligence); difference-similitude matrix; incremental machine learning theorem; knowledge acquisition; knowledge reduction; Data mining; Databases; Information systems; Knowledge acquisition; Learning systems; Machine learning; Machine learning algorithms; Mathematics; Optimization methods; Set theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN
0-7803-8403-2
Type
conf
DOI
10.1109/ICMLC.2004.1382164
Filename
1382164
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