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Data mining and predictive analytics / Daniel T. Larose and Chantal D. Larose.

By: Contributor(s): Material type: TextTextSeries: Wiley series on methods and applications in data miningPublication details: New Jersey : John Wiley & Sons Inc., c2015.Edition: 2nd edDescription: xxix, 794 p. : illustrations ; 25 cmISBN:
  • 9781118116197
Subject(s): DDC classification:
  • 006.312 23 L331
Contents:
Part I: Data prepatation-- Part II: Statistical analysis-- Part III: Classification-- Part IV: Clustering-- Part V: Association rules-- Part VI: Enhancing model performance-- Part VII: Further topics-- Part VIII: Case study: predicting response to direct-mail marketing-- Appendix-- Index.
Summary: 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 will appeal to computer science and statistic students, as well as students in MBA programs, and chief executives.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books ISI Library, Kolkata 006.312 L331 (Browse shelf(Opens below)) Available 136559
Total holds: 0

Includes bibliographical references and index.

Part I: Data prepatation--
Part II: Statistical analysis--
Part III: Classification--
Part IV: Clustering--
Part V: Association rules--
Part VI: Enhancing model performance--
Part VII: Further topics--
Part VIII: Case study: predicting response to direct-mail marketing--
Appendix--
Index.

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

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