9783319377315 - data preprocessing in data mining: 72 di garcía, salvador; luengo, julián; herrera, francisco (9 risultati)
Lingua: Inglese
Editore: Springer, 2016
Serie: Libro 47 di 188 - Intelligent Systems Reference Library
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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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Lingua: Inglese
Editore: Springer, 2016
Serie: Libro 47 di 188 - Intelligent Systems Reference Library
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Da: preigu, Osnabrück, Germaniapreigu
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Taschenbuch. Condizione: Neu. Data Preprocessing in Data Mining | Salvador García (u. a.) | Taschenbuch | Intelligent Systems Reference Library | xv | Englisch | 2016 | Springer | EAN 9783319377315 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot…]com | Anbieter: preigu.
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Lingua: Inglese
Editore: Springer, Springer, 2016
Serie: Libro 47 di 188 - Intelligent Systems Reference Library
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Data Preprocessing for Data Mining addresses one of the most important issues within the well-known Knowledge Discovery from Data process. Data directly taken from the source will likely have inconsistencies, errors or most importantly, it is not…ready to be considered for a data mining process. Furthermore, the increasing amount of data in recent science, industry and business applications, calls to the requirement of more complex tools to analyze it. Thanks to data preprocessing, it is possible to convert the impossible into possible, adapting the data to fulfill the input demands of each data mining algorithm. Data preprocessing includes the data reduction techniques, which aim at reducing the complexity of the data, detecting or removing irrelevant and noisy elements from the data.This book is intended to review the tasks that fill the gap between the data acquisition from the source and the data mining process. A comprehensive look from a practical point of view, including basic concepts and surveying the techniques proposed in the specialized literature, is given.Each chapter is a stand-alone guide to a particular data preprocessing topic, from basic concepts and detailed descriptions of classical algorithms, to an incursion of an exhaustive catalog of recent developments. The in-depth technical descriptions make this book suitable for technical professionals, researchers, senior undergraduate and graduate students in data science, computer science and engineering.
Lingua: Inglese
Editore: Springer-Verlag New York Inc, 2016
Serie: Libro 47 di 188 - Intelligent Systems Reference Library
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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Paperback. Condizione: Brand New. reprint edition. 336 pages. 9.25x6.10x0.76 inches. In Stock.
Lingua: Inglese
Editore: Springer, 2016
Serie: Libro 47 di 188 - Intelligent Systems Reference Library
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Condizione: Brand New. New. US edition. Print on demand title. Delivery takes 20-25 days. Excellent Customer Service.
Lingua: Inglese
Editore: Springer, 2016
Serie: Libro 47 di 188 - Intelligent Systems Reference Library
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Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Condizione: new. Questo è un articolo print on demand.
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Lingua: Inglese
Editore: Springer International Publishing, 2016
Serie: Libro 47 di 188 - Intelligent Systems Reference Library
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Da: moluna, Greven, Germaniamoluna
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Covers the set of techniques under the umbrella of data preprocessing in data mining and machine learningA comprehensive book devoted completely to preprocessing in data miningWritten by experts in the fieldData Prep…rocessing .
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Lingua: Inglese
Editore: Springer, Springer Sep 2016, 2016
Serie: Libro 47 di 188 - Intelligent Systems Reference Library
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Data Preprocessing for Data Mining addresses one of the most important issues within the well-known Knowledge Discovery from Data process. Data directly taken from the source will likely have inconsistencies, errors or most importa…ntly, it is not ready to be considered for a data mining process. Furthermore, the increasing amount of data in recent science, industry and business applications, calls to the requirement of more complex tools to analyze it. Thanks to data preprocessing, it is possible to convert the impossible into possible, adapting the data to fulfill the input demands of each data mining algorithm. Data preprocessing includes the data reduction techniques, which aim at reducing the complexity of the data, detecting or removing irrelevant and noisy elements from the data.This book is intended to review the tasks that fill the gap between the data acquisition from the source and the data mining process. A comprehensive look from a practical point of view, including basic concepts and surveying the techniques proposed in the specialized literature, is given.Each chapter is a stand-alone guide to a particular data preprocessing topic, from basic concepts and detailed descriptions of classical algorithms, to an incursion of an exhaustive catalog of recent developments. The in-depth technical descriptions make this book suitable for technical professionals, researchers, senior undergraduate and graduate students in data science, computer science and engineering. 336 pp. Englisch.
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Lingua: Inglese
Editore: Springer, Springer Sep 2016, 2016
Serie: Libro 47 di 188 - Intelligent Systems Reference Library
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Data Preprocessing for Data Mining addresses one of the most important issues within the well-known Knowledge Discovery from Data process. Data directly taken from the source will likely have inconsistencies, errors or most importantly…, it is not ready to be considered for a data mining process. Furthermore, the increasing amount of data in recent science, industry and business applications, calls to the requirement of more complex tools to analyze it. Thanks to data preprocessing, it is possible to convert the impossible into possible, adapting the data to fulfill the input demands of each data mining algorithm. Data preprocessing includes the data reduction techniques, which aim at reducing the complexity of the data, detecting or removing irrelevant and noisy elements from the data.This book is intended to review the tasks that fill the gap between the data acquisition from the source and the data mining process. A comprehensive look from a practical point of view, including basic concepts and surveying the techniques proposed in the specialized literature, is given.Each chapter is a stand-alone guide to a particular data preprocessing topic, from basic concepts and detailed descriptions of classical algorithms, to an incursion of an exhaustive catalog of recent developments. The in-depth technical descriptions make this book suitable for technical professionals, researchers, senior undergraduate and graduate students in data science, computer science and engineering.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 336 pp. Englisch.
