Articles liés à Data Mining and Predictive Analytics
Synopsis
Data Mining et d'analyse prédictive, 2e édition
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Présentation de l'éditeur
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, Second Edition:
- 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, Second Edition will appeal to computer science and statistic students, as well as students in MBA programs, and chief executives.
Biographie de l'auteur
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.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
- ÉditeurJohn Wiley & Sons Inc
- Date d'édition2015
- ISBN 10 1118116194
- ISBN 13 9781118116197
- ReliureRelié
- Langueanglais
- Numéro d'édition2
- Nombre de pages824
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DATA MINING AND PREDICTIVE ANALYTICS 2ND EDITION
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Data Mining and Predictive Analytics (Wiley Series on Methods and Applications in Data Mining)
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Data Mining and Predictive Analytics (Wiley Series on Methods and Applications in Data Mining)
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Data Mining and Predictive Analytics (Wiley Series on Methods and Applications in Data Mining)
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ISBN 10 : 1118116194
ISBN 13 : 9781118116197
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Data Mining and Predictive Analytics (Wiley Series on Methods and Applications in Data Mining)
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ISBN 13 : 9781118116197
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Data Mining and Predictive Analytics (Wiley Series on Methods and Applications in Data Mining)
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Data Mining and Predictive Analytics
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Data Mining and Predictive Analytics (Hardcover)
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ISBN 10 : 1118116194
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Hardcover. Etat : new. Hardcover. 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781118116197
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Data Mining and Predictive Analytics (Wiley Series on Methods and Applications in Data Mining)
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Data Mining and Predictive Analytics
Edité par
John Wiley & Sons Inc, 2015
ISBN 10 : 1118116194
ISBN 13 : 9781118116197
Neuf
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