Predictive Analytics Data Mining, Machine Learning and Data Science for Practitioners

by Delen, Dursun

• ISBN13: 9780136738510
• ISBN10: 0136738516
• eBook ISBN(s): 9780135946435
• Additional ISBN(s): 9780133551075
• Edition: 2nd
• Format: Paperback
• Copyright: 2020-10-30
• Publisher: Pearson FT Press
• More Book Details
• Purchase Benefits

Summary

Use Predictive Analytics to Uncover Hidden Patterns and Correlations and Improve Decision-Making

Using predictive analytics techniques, decision-makers can uncover hidden patterns and correlations in their data and leverage these insights to improve many key business decisions. In this thoroughly updated guide, Dr. Dursun Delen illuminates state-of-the-art best practices for predictive analytics for both business professionals and students.

Delen provides a holistic approach covering key data mining processes and methods, relevant data management techniques, tools and metrics, advanced text and web mining, big data integration, and much more. Balancing theory and practice, Delen presents intuitive conceptual illustrations, realistic example problems, and real-world case studies—including lessons from failed projects. It is all designed to help you gain a practical understanding you can apply for profit.

* Leverage knowledge extracted via data mining to make smarter decisions
* Use standardized processes and workflows to make more trustworthy predictions
* Predict discrete outcomes (via classification), numeric values (via regression), and changes over time (via time-series forecasting)
* Understand predictive algorithms drawn from traditional statistics and advanced machine learning
* Discover cutting-edge techniques, and explore advanced applications ranging from sentiment analysis to fraud detection

Author Biography

Dr. Dursun Delen holds the William S. Spears Endowed Chair in Business Administration, Patterson Family Endowed Chair in Business Analytics, Director of Research for the Center for Health Systems Innovation, and Regents Professor of Management Science and Information Systems in the Spears School of Business at Oklahoma State University (OSU). As research scientist at Knowledge Based Systems Inc., he led advanced analytics, decision support and information systems research projects funded by DoD, NASA, NIST and DOE. His books include Real World Data Mining: Applied Business Analytics and Decision Making and Advanced Data Mining Techniques. Dr. Delen is editor-in-chief for the Journal of Business Analytics, AI in Business, and International Journal of Experimental Algorithms; senior editor for Decision Support Systems and Decision Sciences, and associate editor for Journal of Business Research, Decision Analytics, and International Journal of RF Technologies. He co-chaired the 4th International Conference on Network Computing and Advanced Information Management.

Table of Contents

Previous Edition's Table of Contents:

Foreword     viii
Chapter 1: Introduction to Analytics     1
Chapter 2: Introduction to Data Mining     31
Chapter 3: The Data Mining Process     67
Chapter 4: Data and Methods in Data Mining     93
Chapter 5: Data Mining Algorithms     141
Chapter 6: Text Analytics and Sentiment Analysis     183
Chapter 7: Big Data Analytics     231
Index     265