Summary of 3_Xgboost
Extreme Gradient Boosting (Xgboost)
- n_jobs: 6
- objective: multi:softprob
- eta: 0.075
- max_depth: 8
- min_child_weight: 5
- 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
36.3 seconds
Metric details
| 0 | 1 | 2 | 3 | 4 | 5 | accuracy | macro avg | weighted avg | logloss | |
|---|---|---|---|---|---|---|---|---|---|---|
| precision | 0.965723 | 0.965894 | 0.970438 | 0.983103 | 0.99232 | 0.997916 | 0.97884 | 0.979233 | 0.97896 | 0.0662399 |
| recall | 0.984159 | 0.960948 | 0.971429 | 0.987654 | 0.989065 | 0.975548 | 0.97884 | 0.978134 | 0.97884 | 0.0662399 |
| f1-score | 0.974854 | 0.963415 | 0.970933 | 0.985373 | 0.99069 | 0.986605 | 0.97884 | 0.978645 | 0.978858 | 0.0662399 |
| support | 2462 | 1562 | 1960 | 1944 | 1829 | 1963 | 0.97884 | 11720 | 11720 | 0.0662399 |
Confusion matrix
| Predicted as 0 | Predicted as 1 | Predicted as 2 | Predicted as 3 | Predicted as 4 | Predicted as 5 | |
|---|---|---|---|---|---|---|
| Labeled as 0 | 2423 | 8 | 5 | 22 | 0 | 4 |
| Labeled as 1 | 2 | 1501 | 52 | 2 | 5 | 0 |
| Labeled as 2 | 7 | 45 | 1904 | 1 | 3 | 0 |
| Labeled as 3 | 21 | 0 | 0 | 1920 | 3 | 0 |
| Labeled as 4 | 11 | 0 | 1 | 8 | 1809 | 0 |
| Labeled as 5 | 45 | 0 | 0 | 0 | 3 | 1915 |
Learning curves
Permutation-based Importance
Confusion Matrix
Normalized Confusion Matrix
ROC Curve
Precision Recall Curve
