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Data Mining for Business Intelligence: Concepts, Techniques, and Applications in R

Data Mining for Business Intelligence: Concepts, Techniques, and Applications in R

Data Mining for Business Intelligence: Concepts, Techniques, and Applications in
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Data Mining for Business Intelligence: Concepts, Techniques, and Applications in R Hardback - 2018 - 1st Edition

by Shmueli, Galit

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WILEY. 1. Acceptable. The item might be beaten up but readable. May contain markings or highlighting, as well as stains, bent corners, or any other major defect, but the text is not obscured in any way.
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Details

  • Title Data Mining for Business Intelligence: Concepts, Techniques, and Applications in R
  • Author Shmueli, Galit
  • Binding Hardback
  • Edition number 1st
  • Edition 1
  • Condition Used - Acceptable
  • Pages 576
  • Volumes 1
  • Language ENG
  • Publisher WILEY
  • Publication date 2018
  • Illustrated Yes
  • Bookseller's Inventory # 1118879368-7-1
  • ISBN 9781118879368 / 1118879368
  • Weight 2.95 lbs (1.34 kg)
  • Dimensions 10.1 x 6.9 x 1.2 in (25.65 x 17.53 x 3.05 cm)
  • Category Mathematics
  • Library of Congress subjects Data mining, Business - Data processing
  • Library of Congress Catalogue Number 2017024503
  • Dewey Decimal Code 658.403
  • Quantity available 1

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Reader reviews for Data Mining for Business Intelligence: Concepts, Techniques, and Applications in R

About the author

Galit Shmueli, PhD, is Distinguished Professor at National Tsing Hua University's Institute of Service Science. She has designed and instructed data mining courses since 2004 at University of Maryland, Statistics.com, Indian School of Business, and National Tsing Hua University, Taiwan. Professor Shmueli is known for her research and teaching in business analytics, with a focus on statistical and data mining methods in information systems and healthcare. She has authored over 70 publications including books.

Peter C. Bruce is President and Founder of the Institute for Statistics Education at Statistics.com. He has written multiple journal articles and is the developer of Resampling Stats software. He is the author of Introductory Statistics and Analytics: A Resampling Perspective (Wiley) and co-author of Practical Statistics for Data Scientists: 50 Essential Concepts (O'Reilly).

Inbal Yahav, PhD, is Professor at the Graduate School of Business Administration at Bar-Ilan University, Israel. She teaches courses in social network analysis, advanced research methods, and software quality assurance. Dr. Yahav received her PhD in Operations Research and Data Mining from the University of Maryland, College Park.

Nitin R. Patel, PhD, is Chairman and cofounder of Cytel, Inc., based in Cambridge, Massachusetts. A Fellow of the American Statistical Association, Dr. Patel has also served as a Visiting Professor at the Massachusetts Institute of Technology and at Harvard University. He is a Fellow of the Computer Society of India and was a professor at the Indian Institute of Management, Ahmedabad, for 15 years.

Kenneth C. Lichtendahl, Jr., PhD, is Associate Professor at the University of Virginia. He is the Eleanor F. and Phillip G. Rust Professor of Business Administration and teaches MBA courses in decision analysis, data analysis and optimization, and managerial quantitative analysis. He also teaches executive education courses in strategic analysis and decision-making, and managing the corporate aviation function.

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