Summary of 9_Xgboost_SelectedFeatures
Extreme Gradient Boosting (Xgboost)
- n_jobs: 6
- objective: multi:softprob
- eta: 0.075
- max_depth: 5
- min_child_weight: 1
- subsample: 1.0
- colsample_bytree: 1.0
- eval_metric: f1
- num_class: 6
- explain_level: 1
Validation
- validation_type: kfold
- k_folds: 5
- shuffle: True
- stratify: True
- random_seed: 42
Optimized metric
f1
Training time
37.1 seconds
Metric details
| 0 | 1 | 2 | 3 | 4 | 5 | accuracy | macro avg | weighted avg | logloss | |
|---|---|---|---|---|---|---|---|---|---|---|
| precision | 0.9708 | 0.967784 | 0.969913 | 0.983632 | 0.99018 | 0.997916 | 0.979863 | 0.980037 | 0.979944 | 0.059119 |
| recall | 0.985784 | 0.961588 | 0.970408 | 0.989198 | 0.992346 | 0.975548 | 0.979863 | 0.979145 | 0.979863 | 0.059119 |
| f1-score | 0.978235 | 0.964676 | 0.970161 | 0.986407 | 0.991262 | 0.986605 | 0.979863 | 0.979557 | 0.979868 | 0.059119 |
| support | 2462 | 1562 | 1960 | 1944 | 1829 | 1963 | 0.979863 | 11720 | 11720 | 0.059119 |
Confusion matrix
| Predicted as 0 | Predicted as 1 | Predicted as 2 | Predicted as 3 | Predicted as 4 | Predicted as 5 | |
|---|---|---|---|---|---|---|
| Labeled as 0 | 2427 | 6 | 5 | 21 | 0 | 3 |
| Labeled as 1 | 2 | 1502 | 51 | 1 | 6 | 0 |
| Labeled as 2 | 9 | 43 | 1902 | 2 | 4 | 0 |
| Labeled as 3 | 15 | 1 | 1 | 1923 | 4 | 0 |
| Labeled as 4 | 4 | 0 | 2 | 7 | 1815 | 1 |
| Labeled as 5 | 43 | 0 | 0 | 1 | 4 | 1915 |
Learning curves
Permutation-based Importance
Confusion Matrix
Normalized Confusion Matrix
ROC Curve
Precision Recall Curve
