Difference between revisions of "Boosting"
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* [http://en.wikipedia.org/wiki/AdaBoost Adaptive Boosting (AdaBoost)] | * [http://en.wikipedia.org/wiki/AdaBoost Adaptive Boosting (AdaBoost)] | ||
* [http://xgboost.readthedocs.io/en/latest/ XGBoost] — uses liner and tree algorithms | * [http://xgboost.readthedocs.io/en/latest/ XGBoost] — uses liner and tree algorithms | ||
| − | * [ | + | * [[LightGBM]] ...Microsoft's gradient boosting framework that uses tree based learning algorithms |
<youtube>5CWwwtEM2TA</youtube> | <youtube>5CWwwtEM2TA</youtube> | ||
Revision as of 13:12, 17 August 2020
Youtube search... ...Google search
- Gradient Descent Optimization & Challenges
- Objective vs. Cost vs. Loss vs. Error Function
- Boosting | Wikipedia
- A Gentle Introduction to the Gradient Boosting Algorithm for Machine Learning | Jason Brownlee
- Ensemble Learning
Gradient Boosting Algorithm uses multiple weak algorithms to create a more powerful accurate algorithm. Instead of using a single estimator, having multiple will create a more stable and robust algorithm. The specialty of Gradient Boosting Algorithms is their higher accuracy. There are several Gradient Boosting Algorithms. 10 Machine Learning Algorithms You need to Know | Sidath Asir @ Medium
- Gradient Boosting Machine (GBM)
- Gradient (Boosted) Decision Tree (GBDT)
- Adaptive Boosting (AdaBoost)
- XGBoost — uses liner and tree algorithms
- LightGBM ...Microsoft's gradient boosting framework that uses tree based learning algorithms
