高技术通讯(英文版)
高技術通訊(英文版)
고기술통신(영문판)
HIGH TECHNOLOGY LETTERS
2003年
3期
24-28
,共5页
谌卫军%Lin Fuzong%Li Jianmin%Zhang Bo
諶衛軍%Lin Fuzong%Li Jianmin%Zhang Bo
심위군%Lin Fuzong%Li Jianmin%Zhang Bo
inductive learning algorithm%machine learning%extension matrix theory
This paper presents a new inductive learning algorithm, HGR (Version 2.0), based on the newly-developed extension matrix theory. The basic idea is to partition the positive examples of a specific class in a given example set into consistent groups, and each group corresponds to a consistent rule which covers all the examples in this group and none of the negative examples. Then a performance comparison of the HGR algorithm with other inductive algorithms, such as C4.5, OC1, HCV and SVM, is given in the paper. The authors not only selected 15 databases from the famous UCI machine learning repository, but also considered a real world problem. Experimental results show that their method achieves higher accuracy and fewer rules as compared with other algorithms.
