Data Mining: Technologies, Techniques, Tools, and Trends
Focusing on a data-centric perspective, this book provides a complete overview of data mining: its uses, methods, current technologies, commercial products, and future challenges. Get and download textbook Data Mining: Technologies, Techniques, Tools, and Trends for free
Taylor & Francis Ltd | 2008 | 336 pages | ISBN-13: 9781420070194 | ISBN-10: 1420070193 | You save 10%
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Three parts divide Data Mining:
Part I describes technologies for data mining - database systems, warehousing, machine learning, visualization, decision support, statistics, parallel processing, and architectural support for data mining
Part II presents tools and techniques - getting the data ready, carrying out the mining, pruning the results, evaluating outcomes, defining specific approaches, examining a specific technique based on logic programming, and citing literature and vendors for up-to-date information
Part III examines emerging trends - min Data Mining new edition
Download free books for Sports Data Mining
Data mining is the process of extracting hidden patterns from data, and it's commonly used in business, bioinformatics, counter-terrorism, and, increasingly, in professional sports. First popularized in Michael Lewis' best-selling Moneyball: The Art of Winning An Unfair Game, it is has become an intrinsic part of all professional sports the world over, from baseball to cricket to soccer. While an industry has developed based on statistical analysis services for any given sport, or even for betting behavior analysis on these sports, no research-level book has considered the subject in any detai
Categories: Early childhood education->Activities, Data mining, Early childhood education->Activitie. Contributors: Ian H. Witten - Author. Format: NOOK Book
Categories: Data mining, Decision support systems. Contributors: Dunja Mladenic - Author. Format: Hardcover
Managing Data Mining Technologies in Organizations: Techniques and Applications: Parag Pendharkar
Data Mining Textbook
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Three parts divide Data Mining:
Part I describes technologies for data mining - database systems, warehousing, machine learning, visualization, decision support, statistics, parallel processing, and architectural support for data mining
Part II presents tools and techniques - getting the data ready, carrying out the mining, pruning the results, evaluating outcomes, defining specific approaches, examining a specific technique based on logic programming, and citing literature and vendors for up-to-date information
Part III examines emerging trends - min
