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 can be used for mining data bases.
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.
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1
Rough sets and data mining: analysis for imprecise data
1997, Kluwer Academic
in English
0792398076 9780792398073
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2
Rough Sets and Data Mining: Analysis of Imprecise Data
November 30, 1996, Springer
Hardcover
in English
- 1 edition
0792398076 9780792398073
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{{cite book|author1=T. Y. Lin |author2=Nick Cercone |date=1997 |title=Rough sets and data mining |publication-place=Boston, Mass |publisher=Kluwer Academic |isbn=0-7923-9807-6 |lccn=96027716 |ol=989427M}}