Presentation	2001/7/12 RDB Expression of Decision Tree, and Knowledge Discovery Supporting System Hiromi Kataoka, Osamu Konishi,
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Abstract(in English)	In this paper, we propose such system that has a relational database translated from the decision tree generated by the decision tree generation algorithm and actually supports the knowledge discovery of a clinical laboratory medicine field using SQL queries. The decision tree has beenwidely used as a tool, which can generate rules from many cases. The C4.5 is a typical decision tree generation algorithm. Recently, the problem of seamless integration of data mining with DBMS is one of the key challenges. We built scalable classification in the form of relations by exploring capabilities of decision trees. The major computation required in this approach can be implemented using standard functions by the relational DBMS. The results of experiments conducted for performance evaluation and analysis are presented.
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Paper #	DE2001-92
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Committee	DE
Conference Date	2001/7/12(1days)
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Registration To	Data Engineering (DE)
Language	JPN
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Title (in English)	RDB Expression of Decision Tree, and Knowledge Discovery Supporting System
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1st Author's Name	Hiromi Kataoka
1st Author's Affiliation	Department of Clinical Laboratory, Kochi Medical School Hospital()
2nd Author's Name	Osamu Konishi
2nd Author's Affiliation	Department of Information Science, Graduate School of Science, Kochi University
Date	2001/7/12
Paper #	DE2001-92
Volume (vol)	vol.101
Number (no)	193
Page	pp.pp.-
#Pages	8
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