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Erschienen in:
2004 | OriginalPaper | Buchkapitel
On Learnability of Decision Tables
verfasst von : Wojciech Ziarko
Erschienen in: Rough Sets and Current Trends in Computing
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
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The article is exploring the learnabilty issues of decision tables acquired from data within the frameworks of rough set and of variable precision rough set models. Measures of learning problem complexity and of learned table domain coverage are proposed. Several methods for enhancing the learnabilty of decision tables are discussed, including a new technique based on value reducts.