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XGBoost algorithm

XL Xiaoting Liu
CF Chenhao Fang
CW Chao Wu
JY Jianxing Yu
QZ Qi Zhao
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XGBoost stands for “Extreme Gradient Boosting” which is a superior implementation of gradient boosted decision trees designed for speed and performance proposed by Chen and Guestrin [27]. The algorithm is optimized in the utilization of computations resources; thus, it has been widely used and well evaluated in machine learning competitions. As the original algorithm, the Gradient boosted decision trees algorithm is also an ensemble learning algorithm using a decision tree as the base learner, but it uses a boosting method in which each tree attempts to minimize the errors of the previous tree and decide final classification with different importance or weights [28].

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