Rough Sets and Data Mining
Analysis of Imprecise Data
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Author
Contributions
- Cercone, N. - Contributor
Publication
1996 - Springer US, Boston, MA, Massachusetts
Language
English
Word Count
113,000 words, Guess
Page Count
452 pages
Physical Format
Electronic resource
Identifiers
- Internet Archiveroughsetsdatamin00lint
- ISBN-101461314615
- ISBN-139781461314615
- OCLC Control Number840281386
- Better World Books9781461314615
and 1 more
- Open LibraryOL27086002M
Classifications
- LCCQ334-342
Description
<Em>Rough Sets and Data Mining: Analysis of Imprecise Data</em> 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. <br/> 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. <br/> <em>Rough Sets and Data Mining: Analysis of Imprecise Data</em> 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.
Subjects
Links
Other Editions
- Rough Sets and Data Mining: Analysis of Imprecise Data
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