Difference between revisions of "LightGBM"
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* [[Capabilities]] | * [[Capabilities]] | ||
* [[Gradient Boosting Machine (GBM)]] | * [[Gradient Boosting Machine (GBM)]] | ||
| + | * [[XGBoost; eXtreme Gradient Boosted trees]] | ||
* [[Multiclassifiers; Ensembles and Hybrids; Bagging, Boosting, and Stacking]] | * [[Multiclassifiers; Ensembles and Hybrids; Bagging, Boosting, and Stacking]] | ||
* [[(Boosted) Decision Tree]] | * [[(Boosted) Decision Tree]] | ||
Revision as of 12:02, 17 August 2020
YouTube search... ...Google search
- AI Solver
- Capabilities
- Gradient Boosting Machine (GBM)
- XGBoost; eXtreme Gradient Boosted trees
- Multiclassifiers; Ensembles and Hybrids; Bagging, Boosting, and Stacking
- (Boosted) Decision Tree
- Boosted Random Forest
- Boosting | Wikipedia
- Boosted Decision Tree Regression | Microsoft
Microsoft's gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed and efficient by using histogram-based algorithms, which bucket continuous feature (attribute) values into discrete bins. This speeds up training and reduces memory usage.
