The most thorough and up-to-date introduction to data mining techniques using SAS Enterprise Miner.
The Sample, Explore, Modify, Model, and Assess (SEMMA) methodology of SAS Enterprise Miner is an extremely valuable analytical tool for making critical business and marketing decisions. Until now, there has been no single, authoritative book that explores every node relationship and pattern that is a part of the Enterprise Miner software with regard to SEMMA design and data mining analysis.
Data Mining Using SAS Enterprise Miner introduces readers to a wide variety of data mining techniques and explains the purpose of-and reasoning behind-every node that is a part of the Enterprise Miner software. Each chapter begins with a short introduction to the assortment of statistics that is generated from the various nodes in SAS Enterprise Miner v4.3, followed by detailed explanations of configuration settings that are located within each node. Features of the book include:
This book is a well-crafted study guide on the various methods employed to randomly sample, partition, graph, transform, filter, impute, replace, cluster, and process data as well as interactively group and iteratively process data while performing a wide variety of modeling techniques within the process flow of the SAS Enterprise Miner software. Data Mining Using SAS Enterprise Miner is suitable as a supplemental text for advanced undergraduate and graduate students of statistics and computer science and is also an invaluable, all-encompassing guide to data mining for novice statisticians and experts alike.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Randall Matignon, MS, is Senior Clinical SAS / Microsoft Office VBA Programmer for Amgen, Inc. in San Francisco, California. He has over twenty years of experience as a statistical programmer and applications developer in the pharmaceutical, healthcare, and biotechnology industries, and he has a broad knowledge of several programming languages, including SAS, S-Plus, and PL-SQL.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Etat : Sehr gut. Zustand: Sehr gut | Seiten: 584 | Sprache: Englisch | Produktart: Bücher | Data Mining Using SAS(r) Enterprise Miner introduces the reader to a wide variety of data mining techniques in SAS(r) Enterprise Miner. This first-of-a-kind book explains the purpose of -- and reasoning behind -- every node that is a part of Enterprise Miner with regard to SEMMA design and data mining analysis. Each chapter starts with a short introduction to the assortment of statistics that are generated from the various Enterprise Miner nodes, followed by detailed explanations of configuration settings that are located within each node. The end result of the author's meticulous presentation is a well crafted study guide on the various methods that one employs to both randomly sample and partition data within the process flow of SAS(r) Enterprise Miner. N° de réf. du vendeur 3695198/2
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Etat : Hervorragend. Zustand: Hervorragend | Seiten: 584 | Sprache: Englisch | Produktart: Bücher | Data Mining Using SAS(r) Enterprise Miner introduces the reader to a wide variety of data mining techniques in SAS(r) Enterprise Miner. This first-of-a-kind book explains the purpose of -- and reasoning behind -- every node that is a part of Enterprise Miner with regard to SEMMA design and data mining analysis. Each chapter starts with a short introduction to the assortment of statistics that are generated from the various Enterprise Miner nodes, followed by detailed explanations of configuration settings that are located within each node. The end result of the author's meticulous presentation is a well crafted study guide on the various methods that one employs to both randomly sample and partition data within the process flow of SAS(r) Enterprise Miner. N° de réf. du vendeur 3695198/1
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