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Author Shmueli, Galit, 1971- author.

Title Data mining for business analytics : concepts, techniques, and applications with JMP Pro / Galit Shmueli, Peter C. Bruce, Mia L. Stephens, Nitin R. Patel.

Publication Info. Hoboken, New Jersey : John Wiley & Sons, 2017.
Š2017

Copies

Location Call No. OPAC Message Status
 Axe Books 24x7 IT E-Book  Electronic Book    ---  Available
Edition First edition.
Description 1 online resource (xxii, 442 pages) : illustrations
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Series ITpro collection
Note "with website."
"Errata: Page 43: Paragraph starting with "Google" is listed twice."--JMP website.
Bibliography Includes bibliographical references (pages 431-432) and index.
Note Online resource; title from e-book title screen (EBL platform, viewed January 31, 2017).
Summary Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP ProŽ presents an applied and interactive approach to data mining. Featuring hands-on applications with JMP ProŽ, a statistical package from the SAS Institute, the book uses engaging, real-world examples to build a theoretical and practical understanding of key data mining methods, especially predictive models for classification and prediction. Topics include data visualization, dimension reduction techniques, clustering, linear and logistic regression, classification and regression trees, discriminant analysis, naive Bayes, neural networks, uplift modeling, ensemble models, and time series forecasting. Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP ProŽ also includes: Detailed summaries that supply an outline of key topics at the beginning of each chapter; End-of-chapter examples and exercises that allow readers to expand their comprehension of the presented material; Data-rich case studies to illustrate various applications of data mining techniques; A companion website with over two dozen data sets, exercises and case study solutions, and slides for instructors. Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP ProŽ is an excellent textbook for advanced undergraduate and graduate-level courses on data mining, predictive analytics, and business analytics. The book is also a one-of-a-kind resource for data scientists, analysts, researchers, and practitioners working with analytics in the fields of management, finance, marketing, information technology, healthcare, education, and any other data-rich field.--Publisher website.
Contents Overview of the data mining process -- Data visualization -- Dimension reduction -- Evaluating predictive performance -- Multiple linear regression -- K-nearest neighbors (kNN) -- The naive Bayes classifier -- Classification and regression trees -- Logistic regression -- Neural nets -- Discriminant analysis -- Combining methods : ensembles and uplift modeling -- Cluster analysis -- Handling time series -- Regression-based forecasting -- Smoothing methods -- Cases.
Subject JMP (Computer file)
JMP (Computer file) (OCoLC)fst01385779
Business mathematics -- Computer programs.
Business -- Data processing.
Data mining.
Business -- Data processing. (OCoLC)fst00842293
Business mathematics -- Computer programs. (OCoLC)fst00842783
Data mining. (OCoLC)fst00887946
COMPUTERS / General
Data Mining
Business Intelligence
Genre/Form Electronic books.
Added Author Bruce, Peter C., 1953- author.
Stephens, Mia L., author.
Patel, Nitin R. (Nitin Ratilal), author.
Other Form: Print version: Shmueli, Galit, 1971- Data mining for business analytics. Hoboken, New Jersey : John Wiley & Sons, 2016 9781118877432 (DLC) 2015048305 (OCoLC)939596191
ISBN 9781118956625 (electronic bk.)
1118956621 (electronic bk.)
9781118877524 (electronic bk.)
1118877527 (electronic bk.)
1118877527
9781118877432 (cloth)
1118877438 (cloth)

 
    
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