Book

Hands-On Ensemble Learning with R

This book introduces you to the concept of ensemble learning and demonstrates how different machine learning algorithms can be combined to build efficient machine learning models. Use R to implement the popular trilogy of ensemble techniques, i.e. bagging, random forest and boosting, to build faster and more accurate machine learning models.

Offered byPackt Logo

Difficulty Level
Intermediate
Completion Time
12h32m approx.
Language
English
Certification
Not available

About Course

Book Content

chapters 12h32m total length

1. Introduction to Ensemble Techniques
2. Bootstrapping
3. Bagging
4. Random Forests
5. The Bare Bones Boosting Algorithms
6. Boosting Refinements
7. The General Ensemble Technique
8. Ensemble Diagnostics
9. Ensembling Regression Models
10. Ensembling Survival Models
11. Ensembling Time Series Models
12. What's Next?

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