Data mining essentially relies on several mathematical disciplines, many of which are presented in this second edition of this book. 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.
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.
Get Mathematical Tools for Data Mining by Chabane Djeraba, Dan A. Simovici at the best price and quality guaranteed only at Werezi Africa's largest book ecommerce store. The book was published by Springer London Ltd and it has 831 pages.
Our digital collection is currently being curated to ensure the best possible reading experience on Werezi. We'll be launching our Ebooks platform shortly.
Your privacy, your choice
Make Werezi work for you
We use essential cookies for your cart and sign-in. With your permission, optional cookies help us understand how Werezi is used and improve your book recommendations.
Essential cookies are always active. Optional analytics stay off unless you choose Allow all.