Free shipping on orders over 19,990 Ft via Packeta, Fox Post Box, and DPD Collection Point

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

Free delivery for purchases over 19 990 Ft

DPD courier 1 190 Ft Hungarian Post 1 795 Ft Hungarian Post 1 690 Ft Hungarian Post 1 690 Ft FoxPost 1 190 Ft Packeta point 1 190 Ft DPD point 990 Ft GLS courier 1 690 Ft GLS point 1 190 Ft

Contact

How to shop

Help

My account

▸ Empty :-(

Free shipping on orders over 19,990 Ft via Packeta, Fox Post Box, and DPD Collection Point

Quality Measures in Data Mining

Name: Quality Measures in Data Mining
Brand: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
SKU: 01564773
Price: 63538 HUF
Availability: InStock
Author: Fabrice Guillet
ISBN: 9783540449119

Fabrice Guillet

Howard J. Hamilton

Language

English

Book Hardback

Libristo code: 01564773

Publishers Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, January 2007

Data mining analyzes large amounts of data to discover knowledge relevant to decision making. Typica... Full description

Libristo code: 01564773

437 b

63 538 Ft

Low in stock at our supplier Shipping in 11-15 days

Up to 30 days for returns

Customers also purchased

Nevlastná sestra Jennifer Donnellyová

Hardback

4 471 Ft

Samariteranstalten Fürstenwalde Jens C. Franze

Hardback

9 915 Ft

L'essentiel de la méthodologie juridique Bonnet

Paperback

5 866 Ft

condominio Andrea Pamparana

Paperback

10 016 Ft

Věci mezi lidmi a byty David Budai

Paperback

1 060 Ft

SHE LIKES HOMOS, NOT ME Nº 02/03 ASAHARA

Book

4 572 Ft

À la découverte des annales akashiques - Comprendre nos vies antérieures pour libérer les blocages e Emily Nicolle

Paperback

8 079 Ft

Manuel Pratique Et Elementaire Des Poids Et Mesures, Des Monnaies, Et Du Calcul Decimal TARBE DES SABLONS-S-

Paperback

11 806 Ft

El Evangelio según el espiritismo Allan Kardec

Paperback

6 638 Ft

Data mining analyzes large amounts of data to discover knowledge relevant to decision making. Typically, numerous pieces of knowledge are extracted by a data mining system and presented to a human user, who may be a decision-maker or a data-analyst. The user is confronted with the task of selecting the pieces of knowledge that are of the highest quality or interest according to his or her preferences. Since this selection is sometimes a daunting task, designing quality and interestingness measures has become an important challenge for data mining researchers in the last decade.§This volume presents the state of the art concerning quality and interestingness measures for data mining. The book summarizes recent developments and presents original research on this topic. The chapters include surveys, comparative studies of existing measures, proposals of new measures, simulations, and case studies. Both theoretical and applied chapters are included. Papers for this book were selected and reviewed for correctness and completeness by an international review committee.