TY - BOOK AU - Olson, David L AU - Dash Wu, Desheng AU - Luo, Cuicui AU - Nabavi, Majid TI - Business analytics with R and python T2 - AI for Risks SN - 9789819747719 U1 - 658.4 PY - 2024/// CY - Singapore PB - Springer KW - Business--Data processing KW - Data mining N1 - Table of content: Data Mining in Business David L. Olson, Desheng Dash Wu, Cuicui Luo, Majid Nabavi Pages 1-7 Data Mining Processes David L. Olson, Desheng Dash Wu, Cuicui Luo, Majid Nabavi Pages 9-21 Data Mining Software David L. Olson, Desheng Dash Wu, Cuicui Luo, Majid Nabavi Pages 23-40 Association Rules David L. Olson, Desheng Dash Wu, Cuicui Luo, Majid Nabavi Pages 41-62 Cluster Analysis David L. Olson, Desheng Dash Wu, Cuicui Luo, Majid Nabavi Pages 63-98 Regression Algorithms in Data Mining David L. Olson, Desheng Dash Wu, Cuicui Luo, Majid Nabavi Pages 99-124 Classification Tools David L. Olson, Desheng Dash Wu, Cuicui Luo, Majid Nabavi Pages 125-163 Variable Selection David L. Olson, Desheng Dash Wu, Cuicui Luo, Majid Nabavi Pages 165-179 Dataset Balancing David L. Olson, Desheng Dash Wu, Cuicui Luo, Majid Nabavi Pages 181-193 Correction to: Business Analytics with R and Python David L. Olson, Desheng Dash Wu, Cuicui Luo, Majid Nabavi Pages C1-C1 Back Matter Pages 195-196 [https://link.springer.com/book/10.1007/978-981-97-4772-6] N2 - This book provides an overview of data mining methods in the field of business. Business management faces challenges in serving customers in better ways, in identifying risks, and analyzing the impact of decisions. Of the three types of analytic tools, descriptive analytics focuses on what has happened and predictive analytics extends statistical and/or artificial intelligence to provide forecasting capability. Chapter 1 provides an overview of business management problems. Chapter 2 describes how analytics and knowledge management have been used to better cope with these problems. Chapter 3 describes initial data visualization tools. Chapter 4 describes association rules and software support. Chapter 5 describes cluster analysis with software demonstration. Chapter 6 discusses time series analysis with software demonstration. Chapter 7 describes predictive classification data mining tools. Applications of the context of management are presented in Chapter 8. Chapter 9 covers prescriptive modeling in business and applications of artificial intelligence. (https://link.springer.com/book/10.1007/978-981-97-4772-6) ER -