Data Mining Using SAS Enterprise Miner

Data Mining Using SAS Enterprise Miner
Author: Randall Matignon
Publisher: John Wiley & Sons
Total Pages: 584
Release: 2007-08-03
Genre: Mathematics
ISBN: 0470149019

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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.

Introduction to Data Mining Using SAS Enterprise Miner

Introduction to Data Mining Using SAS Enterprise Miner
Author: Patricia B. Cerrito
Publisher: SAS Press
Total Pages: 0
Release: 2006
Genre: Data mining
ISBN: 9781590478295

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"This manual provides a general, practical introduction to data mining using SAS Enterprise Miner and SAS Text Miner software"--Preface.

Data Mining Using SAS Enterprise Miner

Data Mining Using SAS Enterprise Miner
Author: SAS Institute
Publisher: Sas Inst
Total Pages: 127
Release: 2003
Genre: Computers
ISBN: 9781590471906

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Predictive Modeling with SAS Enterprise Miner

Predictive Modeling with SAS Enterprise Miner
Author: Kattamuri S. Sarma
Publisher: SAS Institute
Total Pages: 574
Release: 2017-07-20
Genre: Computers
ISBN: 163526040X

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« Written for business analysts, data scientists, statisticians, students, predictive modelers, and data miners, this comprehensive text provides examples that will strengthen your understanding of the essential concepts and methods of predictive modeling. »--

Decision Trees for Business Intelligence and Data Mining

Decision Trees for Business Intelligence and Data Mining
Author: Barry De Ville
Publisher: SAS Press
Total Pages: 224
Release: 2006
Genre: Business & Economics
ISBN: 9781590475676

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This example-driven guide illustrates the application and operation of decision trees in data mining, business intelligence, business analytics, prediction, and knowledge discovery. It explains in detail the use of decision trees as a data mining technique and how this technique complements and supplements other business intelligence applications.

Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner

Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner
Author: Olivia Parr-Rud
Publisher: SAS Institute
Total Pages: 182
Release: 2014-10
Genre: Business & Economics
ISBN: 1629593273

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This tutorial for data analysts new to SAS Enterprise Guide and SAS Enterprise Miner provides valuable experience using powerful statistical software to complete the kinds of business analytics common to most industries. This beginnner's guide with clear, illustrated, step-by-step instructions will lead you through examples based on business case studies. You will formulate the business objective, manage the data, and perform analyses that you can use to optimize marketing, risk, and customer relationship management, as well as business processes and human resources. Topics include descriptive analysis, predictive modeling and analytics, customer segmentation, market analysis, share-of-wallet analysis, penetration analysis, and business intelligence. --

Handbook of Statistical Analysis and Data Mining Applications

Handbook of Statistical Analysis and Data Mining Applications
Author: Ken Yale
Publisher: Elsevier
Total Pages: 824
Release: 2017-11-09
Genre: Mathematics
ISBN: 0124166458

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Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. Includes input by practitioners for practitioners Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models Contains practical advice from successful real-world implementations Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications

Customer Segmentation and Clustering Using SAS Enterprise Miner, Third Edition

Customer Segmentation and Clustering Using SAS Enterprise Miner, Third Edition
Author: Randall S. Collica
Publisher: SAS Institute
Total Pages: 356
Release: 2017-03-23
Genre: Business & Economics
ISBN: 1629605298

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Résumé : A working guide that uses real-world data, this step-by-step resource will show you how to segment customers more intelligently and achieve the one-to-one customer relationship that your business needs. --

Unknown MIR Title

Unknown MIR Title
Author: SAS Publishing
Publisher:
Total Pages:
Release: 2001-03
Genre:
ISBN: 9781590477380

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Text Mining and Analysis

Text Mining and Analysis
Author: Dr. Goutam Chakraborty
Publisher: SAS Institute
Total Pages: 340
Release: 2014-11-22
Genre: Computers
ISBN: 1612907873

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Big data: It's unstructured, it's coming at you fast, and there's lots of it. In fact, the majority of big data is text-oriented, thanks to the proliferation of online sources such as blogs, emails, and social media. However, having big data means little if you can't leverage it with analytics. Now you can explore the large volumes of unstructured text data that your organization has collected with Text Mining and Analysis: Practical Methods, Examples, and Case Studies Using SAS. This hands-on guide to text analytics using SAS provides detailed, step-by-step instructions and explanations on how to mine your text data for valuable insight. Through its comprehensive approach, you'll learn not just how to analyze your data, but how to collect, cleanse, organize, categorize, explore, and interpret it as well. Text Mining and Analysis also features an extensive set of case studies, so you can see examples of how the applications work with real-world data from a variety of industries. Text analytics enables you to gain insights about your customers' behaviors and sentiments. Leverage your organization's text data, and use those insights for making better business decisions with Text Mining and Analysis. This book is part of the SAS Press program.