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

Association Rule Mining

Name: Association Rule Mining
Brand: Springer, Berlin
SKU: 01564252
Price: 19766 HUF
Availability: InStock
Author: Chengqi Zhang
ISBN: 9783540435334

Models and Algorithms

Chengqi Zhang

Shichao Zhang

Language

English

Book Paperback

Libristo code: 01564252

Publishers Springer, Berlin, November 2001

Due to the popularity of knowledge discovery and data mining, in practice as well as among academic... Full description

Libristo code: 01564252

136 b

19 766 Ft

In stock at our supplier Shipping in 5-8 days

Up to 30 days for returns

Customers also purchased

Contemporary Japanese Architecture (English, French, German) Jodidio

Hardback

25 733 Ft

48 законов власти Роберт Грин

Hardback

7 730 Ft

Probleme und Entscheidungswirkungen der neuen Abgeltungsteuer fur Kapitaleinkunfte Martin Knebusch

Paperback

16 520 Ft

Wirtschaftssystem und Industrialisierung in den Entwicklungsländern. Horst Effenberger

Paperback

15 152 Ft

Due to the popularity of knowledge discovery and data mining, in practice as well as among academic and corporate R&D professio- nals, association rule mining is receiving increasing attention. The authors present the recent progress achieved in mining quan- titative association rules, causal rules, exceptional rules, ne- gative association rules, association rules in multi-databases, and association rules in small databases. This book is written for researchers, professionals, and students working in the fields of data mining, data analysis, machine learning, knowled- ge discovery in databases, and anyone who is interested in asso- ciation rule mining.