Stock photo: cover may vary
Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics (Advanced Information and Knowledge Processing) Hardback - 2014
by Simovici, Dan A
- Used
A$279.60
A$17.50
Delivery to USA
Standard delivery: 14 to 21 days
More delivery options
Standard delivery: 14 to 21 days
Ships from Phatpocket Limited (Essex, United Kingdom)
Details
- Title Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics (Advanced Information and Knowledge Processing)
- Author Simovici, Dan A
- Binding Hardback
- Condition Used - Good
- Pages 831
- Volumes 1
- Language ENG
- Publisher Springer
- Publication date 2014-04-09
- Illustrated Yes
- Features Illustrated
- Bookseller's Inventory # Z1-F-072-00417
- ISBN 9781447164067 / 1447164067
- Weight 2.75 lbs (1.25 kg)
- Dimensions 9.2 x 6.2 x 1.9 in (23.37 x 15.75 x 4.83 cm)
-
Themes
- Aspects (Academic): Science/Technology Aspects
- Category Computers - Data Base Management
- Dewey Decimal Code 004.015
About Phatpocket Limited Essex, United Kingdom
Biblio member since 2006
Phatpocket Limited is a world class secondhand bookstore located in the Hertfordshire countryside in the United Kingdom. We specialize in textbooks across an enormous variety of subjects. We aim to provide a low cost source of high quality textbooks to the academic community. We also have a sizable collection of rare and collectible books.
We are dedicated to providing our customers with the highest standard of customer service in the bookselling business.
Books are usually shipped in 48 hours or less. All of our books have a 14 day no hassle money back guarantee unless stated otherwise in the book's description. Item must be returned in the exact same condition that it was received. Through our work with The Rainbow Centre and other Charity Partners, we have already given hundreds of young people in Sri Lanka and Africa the vital chance to get an education.
Reader reviews for Mathematical Tools for Data Mining: Set Theory, Partial Orders, Combinatorics (Advanced Information and Knowledge Processing)
Write a review for this book
Important Terms and Guidelines
- Please focus on the book’s content and context. Also, add any personal comments as to how you enjoyed the book. Substantiate your likes and dislikes. You may make comparisons to other books.
- Reviews must be at least 140 characters in length.
- Please do not reveal critical plot elements.
- This is not a help line. Contact customer support if you need help.
Your review must not include:
- Obscenities, discriminatory language, or other insulting language not suitable for public domain
- Advertisements, “spam” content, or references to other products, offers or websites.
- Email addresses, URLs, phone numbers, physical addresses or other contact information.
- Overly critical comments about other reviews or reviewers
- Time-sensitive material (i.e. promotional tours, seminars, lectures, etc.)
- Availability, price, or alternative ordering/shipping information
From the publisher
From the rear cover
Data mining essentially relies on several mathematical disciplines, many of which are presented in this second edition of this book. Topics include partially ordered sets, combinatorics, general topology, metric spaces, linear spaces, graph theory. To motivate the reader a significant number of applications of these mathematical tools are included ranging from association rules, clustering algorithms, classification, data constraints, logical data analysis, etc. The book is intended as a reference for researchers and graduate students.
The current edition is a significant expansion of the first edition. We strived to make the book self-contained, and only a general knowledge of mathematics is required. More than 700 exercises are included and they form an integral part of the material. Many exercises are in reality supplemental material and their solutions are included.
