Data Mining for Business Analytics: Concepts, Techniques, and Applications in R presents an applied approach to data mining concepts and methods, using R software for illustration. This volume enables readers to implement a variety of popular data mining algorithms in R—a free and open-source software—to tackle complex business problems and identify new opportunities. As a significant update in this successful series, this is the first version to utilize R, covering both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining, and network analysis.
The text features contributions from authors Inbal Yahav and Casey Lichtendahl, who bring extensive expertise in teaching business analytics and consulting for both the private and public sectors. The content has been refined with new material based on feedback from instructors and students in MBA, undergraduate, and executive courses. To ensure practical mastery of the material, the book includes more than a dozen real-world case studies and comprehensive end-of-chapter exercises designed to gauge and expand the reader’s competency.
Book Specifications:
- Title: Data Mining for Business Analytics: Concepts, Techniques, and Applications in R
- Author: Galit Shmueli, Kenneth C. Lichtendahl, Jr., Inbal Yahav, Peter C. Bruce, Nitin R. Patel
- Edition: 1st Edition
- Publisher: WILEY
- Publication Date: January 1, 2017
- ISBN-10: 1118879368
- ISBN-13: 978-1118879368