Data mining using SAS Enterprise miner
Our rough guess is there are 146,000 words in this book.
At a pace averaging 250 words per minute, this book will take 9 hours and 44 minutes to read. With a half hour per day, this will take 20 days to read.
How long will it take you?
This book will take an estimated to read at a reading speed averaging words per minute. With 30 minutes per day, this will take to read.
Enter your reading speedYou can take one of our WPM reading speed tests to find your reading speed.
Create a free account to track your reading progress, build your reading list, and set reading goals.
Author
Contributions
- SAS Institute. - Contributor
Publication
2007 - John Wiley, Hoboken, N.J, New Jersey
Language
English
Word Count
146,000 words, Guess
Page Count
584 pages
Identifiers
- Internet Archivedataminingusings00mati_533
- ISBN-139780470149010
- ISBN-100470149019
- LibraryThing4100151
- Goodreads2434930
and 3 more
- Library of Congress Control Number2007005997
- Better World Books9780470149010
- Open LibraryOL17851170M
Classifications
- DDC005.74
- LCCQA76.9.D343 M39 2007
- LCCQA76.9.D343M39 2007
Description
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 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.
Subjects
Links
Other Editions
- Data mining using SAS Enterprise miner
Reader Reviews
No reviews yet for this book.
Be the first to share your thoughts!