Randall Matignon – Data Mining Using SAS Enterprise Miner
Randall Matignon – Data Mining Using SAS Enterprise Miner
Randall Matignon – Data Mining Using SAS Enterprise Miner
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Description
RANDALL MATIGNON – DATA MINING USING SAS ENTERPRISE MINER
SAS enterprise miner is the most thorough and up-to-date introduction to data mining techniques.
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. There hasn’t been a single authoritative book about every relationship and pattern in the software that is used for 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 the software. Each chapter begins with a short introduction to the assortment of statistics that is generated from the various nodes, followed by detailed explanations of configuration settings that are located within each one. The book has features.
- 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
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 is contained Data Mining Using SAS Enterprise Miner is a useful supplemental text for advanced undergraduate and graduate students of statistics and computer science, as well as a guide to data mining for beginners.
Randall Matignon is using SAS enterprise miner.
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