| | Parameter | Description | range |
| | Booster | Booster to use. | ‘gblinear’, ‘gbtree’ | | N_estimators | Number of boosted trees. | 100,200,300,400,500 | | Max_depth | Maximum tree depth for base learners. | 3,4,5,6,7,8 | | Min_child_weight | Maximum delta step we allow each tree’s weight estimation to be. | 1,2,3,4,5,6 | | Gamma | Minimum loss reduction required to make a further partition on a leaf node of the tree. | 0.01, 0.05,0.1,0.2,0.3 | | Subsample | Subsample ratio of the training instance. | 0.6,0.7,0.8,0.9,1 | | Colsample | Subsample ratio of columns when constructing each tree. | 0.6,0.7,0.8,0.9,1 | | Reg_alpha | L1 regularization term on weights | 0.01,0.05,0.1 | | Reg_lambda | L2 regularization term on weights | 0.01,0.05,0.1 | | Learning_rate | Boosting learning rate | 0.01,0.05,0.07,0.1,0.2 |
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