Data Mining and Predictive Analytics (Wiley Series on Methods and Applications in Data Mining)
Language: English
Published by Wiley, 2015
Series: Book 4 of 7 - Wiley Series on Methods and Applications in Data Mining
- Hardcover
- Used
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- Title
- Data Mining and Predictive Analytics (Wiley Series on Methods and Applications in Data Mining)
- Author
- Larose, Daniel T.
- Publisher
- Wiley
- Publication year
- 2015
- Condition
- Good
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 1118116194
- ISBN 13
- 9781118116197
- Edition
- 2nd Edition
- Series
- Book 4 of 7: Wiley Series on Methods and Applications in Data Mining
Learn methods of data analysis and their application to real-world data sets
This updated second edition serves as an introduction to data mining methods and models, including association rules, clustering, neural networks, logistic regression, and multivariate analysis. The authors apply a unified “white box” approach to data mining methods and models. This approach is designed to walk readers through the operations and nuances of the various methods, using small data sets, so readers can gain an insight into the inner workings of the method under review. Chapters provide readers with hands-on analysis problems, representing an opportunity for readers to apply their newly-acquired data mining expertise to solving real problems using large, real-world data sets.
Data Mining and Predictive Analytics:
- Offers comprehensive coverage of association rules, clustering, neural networks, logistic regression, multivariate analysis, and R statistical programming language
- Features over 750 chapter exercises, allowing readers to assess their understanding of the new material
- Provides a detailed case study that brings together the lessons learned in the book
- Includes access to the companion website, www.dataminingconsultant, with exclusive password-protected instructor content
Data Mining and Predictive Analytics will appeal to computer science and statistic students, as well as students in MBA programs, and chief executives.
"Synopsis" may belong to another edition of this title.
About the Author
Chantal D. Larose is an Assistant Professor of Statistics & Data Science at Eastern Connecticut State University (ECSU). She has co-authored three books on data science and predictive analytics. She helped develop data science programs at ECSU and at SUNY New Paltz. She received her PhD in Statistics from the University of Connecticut, Storrs in 2015 (dissertation title: Model-based Clustering of Incomplete Data).
"About the title" may belong to another edition of this title.
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