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Investigation on AQ11, ID3 and the Principle of Discernibility Matrix 被引量：2

Investigation on AQ11, ID3 and the Principle of Discernibility Matrix
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摘要 The principle of discernibility matrix serves as a tool to discuss and analyze two algorithms of traditional inductive machine learning, AQ11 and ID3. The results are: (1) AQ11 and its family can be completely specified by the principle of discernibility matrix; (2) ID3 can be partly, but not naturally, specified by the principle of discernibility matrix; and (3) The principle of discernibility matrix is employed to analyze Cendrowska sample set, and it shows the weaknesses of knowledge representation style of decision tree in theory. The principle of discernibility matrix serves as a tool to discuss and analyze two algorithms of traditional inductive machine learning, AQ11 and ID3. The results are: (1) AQ11 and its family can be completely specified by the principle of discernibility matrix; (2) ID3 can be partly, but not naturally, specified by the principle of discernibility matrix; and (3) The principle of discernibility matrix is employed to analyze Cendrowska sample set, and it shows the weaknesses of knowledge representation style of decision tree in theory.
作者 王珏 崔佳 赵凯
出处 《Journal of Computer Science & Technology》 SCIE EI CSCD 2001年第1期1-12,共12页 计算机科学技术学报（英文版）
基金 This research is partly supported by the National '863' High-Tech Programme (No. 863-306-ZT06-07-1)and NKPSF (G1998030508).
关键词 rough set theorys principle of discernibility matrix inductive ma- chine learning rough set theorys principle of discernibility matrix, inductive ma- chine learning
分类号 TP13 [自动化与计算机技术—控制理论与控制工程]
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Journal of Computer Science & Technology
2001年 第1期

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