NDLI: An efficient inductive learning method for object-oriented database using attribute entropy

Content Provider	IEEE Xplore Digital Library
Author	Yueh-Min Huang Shian-Hua Lin
Copyright Year	1989
Abstract	The data-driven characteristic of the Version Space rule-learning method works efficiently in memory even if the training set is enormous. However, the concept hierarchy of each attribute used to generalize/specialize the hypothesis of a specific/general (S/G) set is processed sequentially and instance by instance, which degrades its performance. As for ID3, the decision tree is generated from the order of attributes according to their entropies to reduce the number of attributes in some of the tree paths. Unlike Version Space, ID3 generates an extremely complex decision tree when the training set is enormous. Therefore, we propose a method called AGE (A_RCH+OG_L+ASE_, where ARCH="Automatic geneRation of Concept Hierarchies", OGL="Optimal Generalization Level", and ASE="Attribute Selection by Entropy"), taking advantages of Version Space and ID3 to learn rules from object-oriented databases (OODBs) with the least number of learning features according to the entropy. By simulations, we found the performance of our learning algorithm is better than both Version Space and ID3. Furthermore, AGE's time complexity and space complexity are both linear with the number of training instances.
Sponsorship	IEEE IEEE Comput. Soc. Tech. Committee on Data Eng IEEE Computer Society
Starting Page	946
Ending Page	951
Page Count	6
File Size	780788
File Format	PDF
ISSN	10414347
Volume Number	8
Issue Number	6
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1996-12-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Learning systems Object oriented databases Entropy Decision trees Degradation Spatial databases Costs Object oriented modeling Knowledge based systems Expert systems
Content Type	Text
Resource Type	Article
Subject	Information Systems Computational Theory and Mathematics Computer Science Applications

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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