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Data mining and predictive analytics Cover Image

E-book

Data mining and predictive analytics

Larose, Daniel T. (author.). Larose, Chantal D., (author.).

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."--

Record details

ISBN: 9781118868706
ISBN: 1118868706
ISBN: 1118868676
ISBN: 9781118868676
ISBN: 9781118116197
ISBN: 1118116194
ISBN: 9781118116197
Physical Description: 1 online resource (1 volume) : illustrations.
remote
Edition: Second edition.
Publisher: Hoboken, New Jersey : John Wiley & Sons, [2015]
Copyright: ©2015

Content descriptions

Bibliography, etc. Note:	Includes bibliographical references and index.
Formatted Contents Note:	3.11 Using EDA to Investigate Correlated Predictor Variables3.12 Summary of Our EDA; The R Zone; R References; Exercises; Chapter 4: Dimension-Reduction Methods; 4.1 Need for Dimension-Reduction in Data Mining; 4.2 Principal Components Analysis; 4.3 Applying PCA to the Houses Data Set; 4.4 How Many Components Should We Extract?; 4.5 Profiling the Principal Components; 4.6 Communalities; 4.7 Validation of the Principal Components; 4.8 Factor Analysis; 4.9 Applying Factor Analysis to the Adult Data Set; 4.10 Factor Rotation; 4.11 User-Defined Composites.
Language Note:	English.
Source of Description Note:	Print version record.