Data Mining and Predictive Analytics

Nonfiction, Computers, Database Management
Cover of the book Data Mining and Predictive Analytics by Daniel T. Larose, Wiley
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Author: Daniel T. Larose ISBN: 9781118868706
Publisher: Wiley Publication: March 16, 2015
Imprint: Wiley Language: English
Author: Daniel T. Larose
ISBN: 9781118868706
Publisher: Wiley
Publication: March 16, 2015
Imprint: Wiley
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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:

Data Mining and Predictive Analytics will appeal to computer science and statistic students, as well as students in MBA programs, and chief executives.

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