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Daniel T. Larose

Data Mining and Predictive Analytics

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Learn methods of data analysis and their application to real-world data setsThis 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… Mehr

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Produktdetails


Weitere Autoren: Larose, Chantal D.
  • ISBN: 978-1-118-11619-7
  • EAN: 9781118116197
  • Produktnummer: 16236524
  • Verlag: Wiley
  • Sprache: Englisch
  • Erscheinungsjahr: 2015
  • Seitenangabe: 824 S.
  • Masse: H25.0 cm x B15.0 cm
  • Auflage: 2. A.

Über den Autor


Daniel T. Larose is Professor of Mathematical Sciences and Director of the Data Mining programs at Central Connecticut State University. He has published several books, including Data Mining the Web: Uncovering Patterns in Web Content, Structure, and Usage (Wiley, 2007) and Discovering Knowledge in Data: An Introduction to Data Mining (Wiley, 2005). In addition to his scholarly work, Dr. Larose is a consultant in data mining and statistical analysis working with many high profile clients, including Microsoft, Forbes Magazine, the CIT Group, KPMG International, Computer Associates, and Deloitte, Inc.Chantal D. Larose is a Ph.D. candidate in Statistics at the University of Connecticut. Her research focuses on the imputation of missing data and model-based clustering. She has taught undergraduate statistics since 2011, and is a statistical consultant for DataMiningConsultant.com, LLC.

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