Summary of 4_Default_Xgboost
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Extreme Gradient Boosting (Xgboost)
- objective: reg:squarederror
- eval_metric: rmse
- eta: 0.075
- max_depth: 6
- min_child_weight: 1
- subsample: 1.0
- colsample_bytree: 1.0
- explain_level: 2
Validation
- validation_type: split
- train_ratio: 0.75
- shuffle: True
Optimized metric
rmse
Training time
93.4 seconds
Metric details:
| Metric |
Score |
| MAE |
0.136617 |
| MSE |
2.01131 |
| RMSE |
1.4182 |
| R2 |
0.998739 |
Learning curves
Permutation-based Importance
SHAP Importance
SHAP Dependence plots
Dependence (Fold 1)
SHAP Decision plots
Top-10 Worst decisions (Fold 1)
Top-10 Best decisions (Fold 1)
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