Data Mining Using SAS Enterprise Miner

Data Mining Using SAS Enterprise Miner

4.11 - 1251 ratings - Source

The most thorough and upa€“toa€“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 ofa€“and reasoning behinda€“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: The exploration of node relationships and patterns using data from an assortment of computations, charts, and graphs commonly used in SAS procedures A stepa€“bya€“step approach to each node discussion, along with an assortment of illustrations that acquaint the reader with the SAS Enterprise Miner working environment Descriptive detail of the powerful Score node and associated SAS code, which showcases the important of managing, editing, executing, and creating customa€“designed Score code for the benefit of fair and comprehensive business decisiona€“making Complete coverage of the wide variety of statistical techniques that can be performed using the SEMMA nodes An accompanying Web site that provides downloadable Score code, training code, and data sets for further implementation, manipulation, and interpretation as well as SAS/IML software programming code This book is a wella€“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, alla€“encompassing guide to data mining for novice statisticians and experts alike.The Code tab is designed to display the internal SEMMA training program to the node that generates the listed output in the ... If the axis variables are all interval- valued responses, then the PROC MEANS procedure listing will display theanbsp;...

Title:Data Mining Using SAS Enterprise Miner
Author:Randall Matignon, SAS Institute
Publisher:John Wiley & Sons - 2007-08-03


You Must CONTINUE and create a free account to access unlimited downloads & streaming