| base_score | | default: 0.5 |
| booster | | default: "gbtree" |
| colsample_bylevel | Subsample ratio of columns for each level | default: 1 |
| colsample_bynode | Subsample ratio of columns for each split | default: 1 |
| colsample_bytree | Subsample ratio of columns when constructing each tree | default: 1 |
| gamma | Minimum loss reduction required to make a further partition on a leaf node of the tree | default: 0 |
| learning_rate | Boosting learning rate (xgb's "eta") | default: 0.1 |
| max_delta_step | Maximum delta step we allow each tree's weight estimation to be | default: 0 |
| max_depth | Maximum tree depth for base learners | default: 3 |
| min_child_weight | Minimum sum of instance weight(hessian) needed in a child | default: 1 |
| missing | Value in the data which needs to be present as a missing value. If
None, defaults to np.nan
importance_type: string, default "gain"
The feature importance type for the feature_importances_ property: either "gain",
"weight", "cover", "total_gain" or "total_cover" | default: null |
| n_estimators | Number of trees to fit | default: 100 |
| n_jobs | Number of parallel threads used to run xgboost. (replaces ``nthread``) | default: 1 |
| nthread | Number of parallel threads used to run xgboost. (Deprecated, please use ``n_jobs``) | default: null |
| objective | Specify the learning task and the corresponding learning objective or
a custom objective function to be used (see note below)
booster: string
Specify which booster to use: gbtree, gblinear or dart | default: "multi:softprob" |
| random_state | Random number seed. (replaces seed) | default: 42 |
| reg_alpha | L1 regularization term on weights | default: 0 |
| reg_lambda | L2 regularization term on weights | default: 1 |
| scale_pos_weight | Balancing of positive and negative weights
base_score:
The initial prediction score of all instances, global bias | default: 1 |
| seed | Random number seed. (Deprecated, please use random_state) | default: null |
| silent | Whether to print messages while running boosting. Deprecated. Use verbosity instead | default: null |
| subsample | Subsample ratio of the training instance | default: 1 |
| verbosity | The degree of verbosity. Valid values are 0 (silent) - 3 (debug) | default: 1 |