E-Book, Englisch, 169 Seiten
Lawrence / D. / Klimberg Contemporary Perspectives in Data Mining
1. Auflage 2017
ISBN: 978-1-64113-056-1
Verlag: Information Age Publishing
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)
E-Book, Englisch, 169 Seiten
ISBN: 978-1-64113-056-1
Verlag: Information Age Publishing
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)
The series, Contemporary Perspectives on Data Mining, is composed of blind refereed scholarly research methods and applications of data mining. This series will be targeted both at the academic community, as well as the business practitione.
Data mining seeks to discover knowledge from vast amounts of data with the use of statistical and mathematical techniques. The knowledge is extracted from this data by examining the patterns of the data, whether they be associations of groups or things, predictions, sequential relationships between time order events or natural group.
Data mining applications are in finance (banking, brokerage, and insurance), marketing (customer relationships, retailing, logistics, and travel), as well as in manufacturing, health care, fraud detection, homeland security, and law enforcement.
Autoren/Hrsg.
Weitere Infos & Material
1;Cover;1
2;Series page;2
3;Contemporary Perspectives in Data Mining: Volume 3;4
4;Library of Congress Cataloging-in-Publication Data;5
5;Contents;6
6;SECTION I: PREDICTIVE ANALYTICS;8
6.1;CHAPTER 1: Bootstrap Aggregation for Neural Network Forecasting of Supply Chain Order Quantity;10
6.2;CHAPTER 2: Combining Retrospective and Predictive Analytics for More Robust Decision Support;36
6.3;CHAPTER 3: Predictive Analytical Model of the CEO Compensation of Major U.S. Corporate Insurance Companies;48
7;SECTION II: BUSINESS APPLICATIONS;54
7.1;CHAPTER 4: Analyzing Operational and Financial Performance of U.S. Hospitals Using Two-Stage Production Process;56
7.2;CHAPTER 5: Digital Disruption;74
7.3;CHAPTER 6: The Hazards of Subgroup Analysis in Randomized Business Experiments and How to Avoid Them;86
7.4;CHAPTER 7: Business Intelligence Challenges for Small and Medium-Sized Business;100
8;SECTION III: TOPICS IN DATA MINING;110
8.1;CHAPTER 8: Data Mining Techniques Applied to Outcome Analysis and Validation for the Futures Drug and Alcohol Rehabilitation Center;112
8.2;CHAPTER 9: An Extended H-Index;142
8.3;CHAPTER 10: Why We Need Analytics Grand Rounds;154
9;ABOUT THE EDITORS;168
