Machine Learning with Bagging and Boosting
- Indbinding:
- Paperback
- Sideantal:
- 58
- Udgivet:
- 4. oktober 2018
- Størrelse:
- 152x3x229 mm.
- Vægt:
- 91 g.
- 8-11 hverdage.
- 11. december 2024
På lager
Forlænget returret til d. 31. januar 2025
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- Ingen binding
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- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
Beskrivelse af Machine Learning with Bagging and Boosting
This book is an exploration of machine learning. It focuses on Bagging and Boosting machine learning algorithms, which belong to the category of ensemble learning. The author helps you firstly familiarize yourself with the ensemble method. The various aspects of the decision tree algorithm have been explored in detail. Then the author guides you on how to create and use bagged trees in machine learning. The random forest algorithm has been discussed in depth. The various types of Boosting algorithms have been explored. The author has given practical examples including mathematics and programming. Each of these examples is accompanied by clear explanation. Here is a preview of what you'll learn: - An Overview of Ensemble Method - Decision Tree Algorithm - Bagging - Random Forest - BoostingTags: bagging machine, boosting machine learning, ensemble machine learning, bagging machine learning, random forest machine learning, tree algorithms, machine learning.
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