Data Mining Using SAS Enterprise Miner

Beschreibung

The most thorough and up-to-date introduction to data miningtechniques using SAS Enterprise Miner. The Sample, Explore, Modify, Model, and Assess (SEMMA)methodology of SAS Enterprise Miner is an extremely valuableanalytical tool for making critical business and marketingdecisions. Until now, there has been no single, authoritative bookthat explores every node relationship and pattern that is a part ofthe Enterprise Miner software with regard to SEMMA design and datamining analysis. Data Mining Using SAS Enterprise Miner introduces readers to awide variety of data mining techniques and explains the purposeof-and reasoning behind-every node that is a part of the EnterpriseMiner software. Each chapter begins with a short introduction tothe assortment of statistics that is generated from the variousnodes in SAS Enterprise Miner v4.3, followed by detailedexplanations of configuration settings that are located within eachnode. Features of the book include: * The exploration of node relationships and patterns using datafrom an assortment of computations, charts, and graphs commonlyused in SAS procedures * A step-by-step approach to each node discussion, along with anassortment of illustrations that acquaint the reader with the SASEnterprise Miner working environment * Descriptive detail of the powerful Score node and associatedSAS code, which showcases the important of managing, editing,executing, and creating custom-designed Score code for the benefitof fair and comprehensive business decision-making * Complete coverage of the wide variety of statisticaltechniques that can be performed using the SEMMA nodes * An accompanying Web site that provides downloadable Scorecode, training code, and data sets for further implementation,manipulation, and interpretation as well as SAS/IML softwareprogramming code This book is a well-crafted study guide on the various methodsemployed to randomly sample, partition, graph, transform, filter,impute, replace, cluster, and process data as well as interactivelygroup and iteratively process data while performing a wide varietyof modeling techniques within the process flow of the SASEnterprise Miner software. Data Mining Using SAS Enterprise Mineris suitable as a supplemental text for advanced undergraduate andgraduate students of statistics and computer science and is also aninvaluable, all-encompassing guide to data mining for novicestatisticians and experts alike.

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Randall Matignon

Themen in »Data Mining Using SAS Enterprise Miner«

Computational & Graphical Statistics Computer Science Data Mining Data Mining Statistics Database & Data Warehousing Technologies Datenbanken u. Data Warehousing Informatik Rechnergestützte u. graphische Statistik SAS Statistics Statistik

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"The book provides a good account of the numerical andcomputational approaches used within the various nodes and explainsnecessary background concepts."(The AmericanStatician, May 2009) "...a very detailed user guide." (MAA Reviews,December 26, 2007)
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