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Data Mining
Krzysztof J. Cios, Witold Pedrycz, Roman W. Swiniarski, Lukasz Andrzej Kurgan (Broschiert, Englisch)
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Beschreibung
“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. 85,59 €
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Technische Daten
Erscheinungsdatum
29.10.2010
Sprache
Englisch
EAN
9781441941206
Herausgeber
Springer US
Sonderedition
Nein
Autor
Krzysztof J. Cios, Witold Pedrycz, Roman W. Swiniarski, Lukasz Andrzej Kurgan
Seitenanzahl
606
Auflage
1
Einbandart
Broschiert
Buch Untertitel
A Knowledge Discovery Approach
Schlagwörter
DOM, LA, OLAP, algorithms, classification, data mining, data security, data warehouse, knowledge discovery, knowledge representation, learning, supervised learning, tools, unsupervised learning
Thema-Inhalt
UN - Datenbanken
UYQ - Künstliche Intelligenz
UNF - Data Mining
UYQE - Wissensbasierte Systeme, Expertensysteme
UNH - Informationsrückgewinnung, Information Retrieval
UND - Data Warehousing
PBT - Wahrscheinlichkeitsrechnung und Statistik
UYQP - Mustererkennung
Höhe
254 mm
Breite
17.8 cm
Hersteller: Springer Nature Customer Service Center GmbH, ProductSafety@springernature.com
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