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Daniel T. Larose

Data Mining and Predictive Analytics

Ebook (PDF Format)

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


  • ISBN: 978-1-118-86867-6
  • EAN: 9781118868676
  • Produktnummer: 19383191
  • Verlag: Wiley
  • Sprache: Englisch
  • Erscheinungsjahr: 2015
  • Seitenangabe: 824 S.
  • Plattform: PDF
  • Masse: 39'774 KB
  • Auflage: 2. Aufl.

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 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).

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