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Published in:
2004 | OriginalPaper | Chapter
On Learnability of Decision Tables
Author : Wojciech Ziarko
Published in: Rough Sets and Current Trends in Computing
Publisher: Springer Berlin Heidelberg
Included 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.