Data Mining and Predictive Analytics 2e
Book Details
Format
Hardback or Cased Book
ISBN-10
1118116194
ISBN-13
9781118116197
Publisher
John Wiley & Sons Inc
Imprint
John Wiley & Sons Inc
Country of Manufacture
US
Country of Publication
GB
Publication Date
Apr 24th, 2015
Print length
824 Pages
Weight
1,308 grams
Dimensions
24.20 x 16.50 x 4.80 cms
Product Classification:
Data mining
Ksh 21,400.00
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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.
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 languageFeatures over 750 chapter exercises, allowing readers to assess their understanding of the new materialProvides a detailed case study that brings together the lessons learned in the bookIncludes 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.
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