Data Mining for Business Analytics: Concepts, Techniques, and Applications in R
Summary: “Data Mining for Business Analytics: Concepts, Techniques, and Applications in R” offers a comprehensive guide to data mining techniques and their applications in business analytics. The book covers key concepts such as data preprocessing, classification, clustering, association analysis, and predictive modeling using the R programming language. It explores how data mining can be used to extract valuable insights from large datasets and drive business decision-making processes. With practical examples, case studies, and hands-on exercises, the text provides readers with the knowledge and skills needed to apply data mining techniques in real-world business scenarios. Whether you’re a student studying business analytics or a business professional seeking to leverage data for competitive advantage, this edition serves as an essential resource for understanding and implementing data mining concepts and techniques.
Author Information: The authors of “Data Mining for Business Analytics: Concepts, Techniques, and Applications in R” are likely experienced data scientists, statisticians, or business analysts with expertise in data mining and analytics.
Publisher: Wiley
Publication Year: 2017
ISBN-10: 1118879368
ISBN-13: 978-1118879368