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: The exploration of node
relationships and patterns using data from an assortment of
computations, charts, and graphs commonly used in SAS procedures A
step-by-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
custom-designed Score code for the benefit of fair and
comprehensive business decision-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
Scorecode, training code, and data sets for further implementation,
manipulation, and interpretation as well as SAS/IML software
programming code
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.
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