- Mastering Predictive Analytics with R Second Edition
- Table of Contents
- Mastering Predictive Analytics with R Second Edition
- Credits
- About the Authors
- About the Reviewer
- www.PacktPub.com
- Customer Feedback
- Preface
- 1. Gearing Up for Predictive Modeling
- Models
- Types of model
- The process of predictive modeling
- Summary
- 2. Tidying Data and Measuring Performance
- 3. Linear Regression
- 4. Generalized Linear Models
- 5. Neural Networks
- 6. Support Vector Machines
- 7. Tree-Based Methods
- 8. Dimensionality Reduction
- Defining DR
- Correlated data analyses
- Scatterplots
- Causation
- The degree of correlation
- Reporting on correlation
- Principal component analysis
- Using R to understand PCA
- Independent component analysis
- Defining independence
- ICA pre-processing
- Factor analysis
- Explore and confirm
- Using R for factor analysis
- The output
- NNMF
- Summary
- Defining DR
- 9. Ensemble Methods
- 10. Probabilistic Graphical Models
- 11. Topic Modeling
- 12. Recommendation Systems
- 13. Scaling Up
- 14. Deep Learning
- Index
Authors
James D. Miller
Rui Miguel Forte
Reviewer
Davor Lozić
Commissioning Editor
Amey Varangaonkar
Acquisition Editor
Divya Poojari
Content Development Editor
Deepti Thore
Technical Editor
Nilesh Sawakhande
Copy Editor
Safis Editing
Project Coordinator
Shweta H Birwatkar
Proofreader
Safis Editing
Indexer
Pratik Shirodkar
Graphics
Tania Dutta
Production Coordinator
Shantanu Zagade
Cover Work
Shantanu Zagade
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