Difference between revisions of "XGBoost; eXtreme Gradient Boosted trees"
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* [[Capabilities]] | * [[Capabilities]] | ||
* [[Boosting]] | * [[Boosting]] | ||
| + | * [[Gradient Boosting Machine (GBM)]] | ||
* [[Random Forest (or) Random Decision Forest]] | * [[Random Forest (or) Random Decision Forest]] | ||
* [[Boosted Random Forest]] | * [[Boosted Random Forest]] | ||
Revision as of 15:23, 27 July 2020
YouTube search... ...Google search
- AI Solver
- Capabilities
- Boosting
- Gradient Boosting Machine (GBM)
- Random Forest (or) Random Decision Forest
- Boosted Random Forest
Random forest (ensemble method) builds multiple decision trees and merges them together to get a more accurate and stable prediction. Random Forest is a flexible, easy to use machine learning algorithm that produces, even without hyper-parameter tuning, a great result most of the time. It is also one of the most used algorithms, because it’s simplicity and the fact that it can be used for both classification and regression tasks. The Random Forest Algorithm | Niklas Donges @ Towards Data Science
