XGBoost stands for extreme gradient boosting. It is a variant of the gradient boosting machine that aims to improve performance and speed. The XGBoost library in Python implements the gradient boosting decision tree algorithm. The name gradient boosting comes from its us of the gradient descent algorithm to minimize loss when adding new models. XGBoost can handle both regression and classification tasks.
XGBoost is the algorithm of choice among those participating in Kaggle competitions because of its performance and speed of execution in difficult machine learning problems.
Some of the important parameters that are used in XGBoost are as follows:
- n_estimators/ntrees: This specifies the number of trees to build. The default value is 50.
- max_depth: This specifies the maximum...
