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- p r e s e n t s -
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Data Mining Using SAS Enterprise Miner (c) by Wiley
The type of the release is: eBook
In the PDF format with ISBN: 0470149019 and Pub Date: August 03, 2007
The size of the release is: 12 disks x 5.00mb
And released on: 10/11/2007
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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 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 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.
http://www.amazon.com/exec/obidos/tg/detail/-/0470149019/
INSTALL NOTES
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