GBDT && XGBOOST
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GBDT && XGBOOST
Outline
Introduction
GBDT Model
XGBOOST Model
GBDT vs. XGBOOST
Experiments
References
Introduction
Gradient Boosting Decision Tree is a machine learning technique for regression and classification problems, which produces a prediction model in the form of an ensemble of basic learning models, typically decision trees.
Decision Tree: e.g.
eXtreme Gradient Boosting (XGBOOST) is an efficient implementation of Gradient Boosting method, a scalable, portable and distributed GB library, and it was started as a research project by Tianqi Chen.
GBDT Model
XGBOOST Model
GBDT vs XGBOOST:
Experiments
References:
1. J. Friedman(1999). Greedy Function Approximation: A Gradient Boosting
Machine.
2. J. Friedman(1999). Stochastic Gradient Boosting.
3. T. Chen, C. Guestrin(2016). XGBoost: A Scalable Tree Boosting System.
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