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Data Mining
Hoofdkenmerken
Auteur: Krzysztof J. Cios; Witold Pedrycz; Roman W. Swiniarski; Lukasz Andrzej Kurgan
Titel: Data Mining
Uitgever: Springer Nature
ISBN: 9780387367958
ISBN boekversie: 9780387333335
Prijs: € 95.91
Verschijningsdatum: 05-10-2007
Inhoudelijke kenmerken
Categorie: General
Taal: English
Imprint: Springer
Technische kenmerken
Verschijningsvorm: E-book
 

Inhoudsopgave:

“If you torture the data long enough, Nature will confess,” said 1991 Nobel-winning economist Ronald Coase. The statement is still true. However, achieving this lofty goal is not easy. First, “long enough” may, in practice, be “too long” in many applications and thus unacceptable. Second, to get “confession” from large data sets one needs to use state-of-the-art “torturing” tools. Third, Nature is very stubborn — not yielding easily or unwilling to reveal its secrets at all. Fortunately, while being aware of the above facts, the reader (a data miner) will find several efficient data mining tools described in this excellent book. The book discusses various issues connecting the whole spectrum of approaches, methods, techniques and algorithms falling under the umbrella of data mining. It starts with data understanding and preprocessing, then goes through a set of methods for supervised and unsupervised learning, and concludes with model assessment, data security and privacy issues. It is this specific approach of using the knowledge discovery process that makes this book a rare one indeed, and thus an indispensable addition to many other books on data mining. To be more precise, this is a book on knowledge discovery from data. As for the data sets, the easy-to-make statement is that there is no part of modern human activity left untouched by both the need and the desire to collect data. The consequence of such a state of affairs is obvious.
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