Synopsis
If you have an abundance of data, but no idea what to do with it, this book was written for you! Packed with examples from an array of industries, Introduction to Data Mining Using SAS Enterprise Miner provides you with excellent starting points and practical guidelines to begin data mining today. Author Patricia Cerrito encourages you to think of data mining as a process of exploration rather than as a collection of tools to investigate data. In that way, you choose the methods that will extract the most information from your data, and, while there are no right answers to investigating data sets, there are many questions that can be asked to produce meaningful results. Each answer then creates a path that helps you drill down to explore the data fully. It is up to you to determine what is of interest and what is important to analyze.
In addition to providing a basic introduction to the processes and techniques of data mining using SAS Enterprise Miner software, the book also addresses:
- Visualizing and summarizing data
- Using clustering, association rules, and predictive modeling
- Using SAS Text Miner software for text analysis
- Writing accurate and effective reports about your data mining results
This book is intended for a broad audience interested in learning about the practical aspects of data mining. Readers should have some basic knowledge of SAS and statistics.
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About the Author
Patricia B. Cerrito is a professor of mathematics at the University of Louisville and a leading authority on data and text mining in disease management. A SAS user since 1973, Patricia is a frequent presenter at regional and national SAS conferences and has served as section co-chair for the South East SAS Users Group (SESUG) and the Pharmaceutical Industry SAS Users Group (PharmaSUG). Patricia holds a doctorate in mathematics from the University of Cincinnati and is an active member of PharmaSUG and the Association for Institutional Research (AIR).
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Introduction to Data Mining Using SAS Enterprise Miner
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Paperback. Condition: Good. No Jacket. Former library book; Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less. Seller Inventory # G1590478290I3N10