Predictive modeling with SAS Enterprise Miner practical solutions for business applications by Kattamuri S. Sarma

Cover of: Predictive modeling with SAS Enterprise Miner | Kattamuri S. Sarma

Published by SAS Institute in Cary, NC .

Written in English

Read online

Subjects:

  • Enterprise miner,
  • SAS (Computer file),
  • Business -- Data processing,
  • Data mining,
  • Regression analysis -- Computer programs,
  • Statistics -- Data processing

Edition Notes

Book details

StatementKattamuri S. Sarma.
SeriesSAS Press series
ContributionsSAS Institute.
Classifications
LC ClassificationsHF5548.2 .S244 2007
The Physical Object
Paginationxii, 360 p. :
Number of Pages360
ID Numbers
Open LibraryOL20637461M
ISBN 101590477030
ISBN 109781590477038
LC Control Number2008295706
OCLC/WorldCa166391448

Download Predictive modeling with SAS Enterprise Miner

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Title: Predictive Modeling with SAS Enterprise Miner: Practical Solutions for Business Applications, Second Edition Created Date: 1/21/ PM. Kattamuri Sarma’s book Predictive Modeling with SAS ® Enterprise Miner is an essential book for data scientists and analysts at all levels.

Students of data science and new professionals will find the book's step by step approach invaluable as they recreate the book's applications. The correct bibliographic citation for this manual is as follows: Sarma, Kattamuri S., Ph.D. Predictive Modeling with SAS® Enterprise Miner™: Practical Solutions for Business Applications, ThirdNC: SAS Institute Inc.

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Develop predictive models quickly, learn how to test numerous models and compare the results, gain an in-depth understanding of predictive models and multivariate methods, and discover how to do in-depth analysis.

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Predictive Modeling with SAS Enterprise Miner: Practical Solutions for Business Applications is destined to become the definitive guide to the use of SAS Enterprise Miner, and should be considered an indispensable resource for modelers who want a better understanding of the software's capabilities.

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Streamline the data mining process and create predictive and descriptive models based on analytics. SAS Enterprise Miner helps you analyze complex data, discover patterns and build models so you can more easily detect fraud, anticipate resource demands and minimize customer attrition.

Predictive Modeling With SAS Enterprise Miner: Practical Solutions for Business Applications October Get Predictive Modeling with SAS Enterprise Miner, 2nd Edition now with O’Reilly online learning. O’Reilly members experience live online training, plus books, videos, and.

This course covers advanced topics using SAS Enterprise Miner including how to optimize the performance of predictive models beyond the basics. The course continues the development of predictive models that begins in the Applied Analytics Using SAS® Enterprise Miner™ course, for example, by making use of the two-stage modeling node.

Description: If you are a graduate student, researcher, or statistician interested in predictive modeling; a data mining expert who wants to learn SAS Enterprise Miner; or a business analyst looking for an introduction to predictive modeling using SAS Enterprise Miner, you'll be able to develop predictive models quickly and effectively using the theory and examples presented in this book.

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O’Reilly members experience live online training, plus books, videos, and digital content from + publishers. Re: Data for predictive modeling with enterprise miner practice test Posted ( views) | In reply to Cynthia_sas A suggestion would be to add the data for the subset of people who do have access to EM through On Demand.

New to the third edition is a chapter that focuses on predictive models within microsegments and combined segments, and a new parallel process technique is introduced using SAS Factory Miner.

In addition, all examples have been updated to the latest version of SAS Enterprise Miner. Kattamuri Sarma's Predictive Modeling with SAS Enterprise Miner: Practical Solutions for Business Applications, Third Edition, will show you how to develop and test predictive models quickly using SAS Enterprise Miner.

Using realistic data, the book explains complex methods in a simple and practical way to readers from different backgrounds and /5(7).

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For analysts who are creating advanced predictive models using big data. Successful candidates should have experience in the following areas: Deploying open source models in SAS; Machine learning and predictive modeling techniques.

Application of machine learning and predictive modeling techniques to big, distributed and in-memory data sets. For the predictive modeling methods in SAS Enterprise Miner, each case in a data set represents a different entity, independent of the other cases in the data set.

If the entities in question are, for example, customers, then all of the information pertaining to any one customer must be contained in a single case in the data set.

Data Mining Using SAS® Enterprise Miner™: A Case Study Approach, Fourth Edition. Search; PDF; EPUB; Feedback; More. Help Tips; Accessibility; Email this page; Settings; About; Table of Contents; Topics; About This Book Tree level 1.

Node 1 of 8. Introduction to SAS Enterprise Miner Tree level 1. Node 2 of 8. Predictive Modeling Tree level 1. Predictive Modeling with SAS Enterprise Miner: Practical Solutions for Business Applications: Sarma, Kattamuri R., Ph.D.: Books - (8).

The book shows how to rapidly develop and test predictive models using SAS ® Enterprise Miner ™. Topics include Logistic Regression, Regression, Decision Trees, Neural Networks, Variable Clustering, Observaton-Clustering, Data Imputation, Binning, Data Exploration, Variable Selection, Variable Transformation, Modeling Binary and continuous.

Predictive Modeling Tree level 2. Node 3 of 4. Predictive Modeling Tree level 3. Node 1 of 1. Enterprise Miner Target Profiler SAS Enterprise Miner Model Deployment Tree level 1.

Node 22 of SAS Credit Scoring Tree level 1. Node 23 of Loading. Loading. Version. SAS® Enterprise Miner™ Reference Help. SAS Enterprise Miner streamlines the data mining process to create highly accurate predictive and descriptive models based on analysis of vast amounts of data from across an enterprise.

Data mining is applicable in a variety of industries and provides methodologies for such diverse business problems as fraud detection, householding, customer retention and attrition, database marketing. Sample, Explore, Modify, Model, and Assess. SAS Enterprise Miner nodes are arranged on tabs with the same names.

• Sample — These nodes identify, merge, partition, and sample input data sets, among other tasks. 6 Chapter 1 • Introduction to SAS Enterprise Miner.

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