Rough Sets and Data Mining: Analysis of Imprecise Data (1997)

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Synopsis
Rough Sets and Data Mining: Analysis of Imprecise Data is an edited collection of research chapters on the most recent developments in rough set theory and data mining. The chapters in this work cover a range of topics that focus on discovering dependencies among data, and reasoning about vague, uncertain and imprecise information. The authors of these chapters have been careful to include fundamental research with explanations as well as coverage of rough set tools that can be used for mining data bases. The contributing authors consist of some of the leading scholars in the fields of rough sets, data mining, machine learning and other areas of artificial intelligence. Among the list of contributors are Z. Pawlak, J Grzymala-Busse, K. Slowinski, and others. Rough Sets and Data Mining: Analysis of Imprecise Data will be a useful reference work for rough set researchers, data base designers and developers, and for researchers new to the areas of data mining and rough sets.
Copyright:
1997

Book Details

Book Quality:
Publisher Quality
ISBN-13:
9781461314615
Related ISBNs:
9780792398073
Publisher:
Springer US
Date of Addition:
Copyrighted By:
N/A
Adult content:
No
Language:
English
Has Image Descriptions:
No
Categories:
Nonfiction, Computers and Internet, Mathematics and Statistics, Philosophy
Submitted By:
Bookshare Staff
Usage Restrictions:
This is a copyrighted book.
Edited by:
T.Y. Lin
Edited by:
N. Cercone

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