Statements (57)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:software_framework
|
| gptkbp:bfsLayer |
4
|
| gptkbp:bfsParent |
gptkb:R_programming_language
|
| gptkbp:based_on |
gradient boosting
|
| gptkbp:developed_by |
gptkb:Tianqi_Chen
|
| gptkbp:first_released |
gptkb:2014
|
| gptkbp:has_feature |
early stopping
regularization feature importance custom objective functions handling missing values |
| gptkbp:has_method |
gptkb:product
learning rate gamma lambda objective function alpha n_estimators colsample_bytree max depth subsample verbosity booster type early_stopping_rounds eval_metric feature_weights interaction_constraints max_bin monotone_constraints scale_pos_weight tree_method |
| gptkbp:has_programs |
gptkb:sports_team
healthcare image processing finance marketing natural language processing bioinformatics recommendation systems time series forecasting anomaly detection |
| https://www.w3.org/2000/01/rdf-schema#label |
xgboost
|
| gptkbp:is_available_in |
gptkb:Java
gptkb:R gptkb:Julia gptkb:Library gptkb:Go gptkb:Skrull |
| gptkbp:is_popular_in |
data science
Kaggle competitions |
| gptkbp:is_used_for |
gptkb:video_game
gptkb:computer regression |
| gptkbp:language |
gptkb:C++
|
| gptkbp:supports |
parallel processing
cross-validation tree pruning |