Check order status

Become part of a community of book lovers from all over the world and get access to a whole bunch of benefits. Create an account for free

DPD courier 4.99 € GLS courier 9.99 €

Contact

How to shop

Help

My account

▸ Empty :-(

Rough Sets and Data Mining

Name: Rough Sets and Data Mining
Brand: Springer
SKU: 01398469
Price: 175.93 EUR
Availability: InStock
Author: T.Y. Lin
ISBN: 9780792398073

Analysis of Imprecise Data

T.Y. Lin

N. Cercone

Language

English

Book Hardback

Libristo code: 01398469

Publishers Springer, November 1996

Rough Sets and Data Mining: Analysis of Imprecise Data is an edited collection of research chapters... Full description

Libristo code: 01398469

425 b

175.93 €

Low in stock at our supplier Shipping in 13-18 days

Up to 30 days for returns

Customers also purchased

Záhadné miesta 4. diel Ján Lacika

Paperback

13.27 €

Care Bears: Pride Bear Funky Chunky Magnet Stationery items

Stationery items

8.50 €

Trio Gesellschaftswissenschaften 5 / 6. Arbeitsheft Basis. Für Berlin und Brandenburg Tatjana Brammer

Sheet

11.04 €

EXPOSITOR A4 ESTIMULACION COGNITIVA NIVEL 1,2,3 (105 CUAD.)

Book

112.08 €

50 Jahre Eminem

Hardback

22.49 €

pene d'amore di Edward Gardiner. Un prequel di Orgoglio & Pregiudizio Nicole Clarkston

Paperback

18.33 €

Jörg Widmann - Experimentelle Kammermusik, 1 DVD Peider A. Defilla

DVD

31.51 €

Ken Jutsu SANTOS NALDA

Paperback

4.35 €

ELIZABETH BATHORY. LA CONDESA SANGRIENTA PASCAL CROCI

Paperback

16.51 €

Tirer et interpréter le Jeu de Mademoiselle Lenormand Renner

Paperback

17.02 €

Albert Einstein, 2 DVDs Lotti Mehnert

DVD

17.93 €

Die Ausschlußfrist im Arbeitsrecht. Hansjörg Weber

Paperback

56.64 €

Der Antrag im Verwaltungsverfahren. Martin Schnell

Paperback

56.64 €

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.