Summary of 4_Xgboost
Extreme Gradient Boosting (Xgboost)
- n_jobs: 6
- objective: multi:softprob
- eta: 0.1
- max_depth: 8
- 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
37.9 seconds
Metric details
| 0 | 1 | 2 | 3 | 4 | 5 | accuracy | macro avg | weighted avg | logloss | |
|---|---|---|---|---|---|---|---|---|---|---|
| precision | 0.9642 | 0.964194 | 0.972862 | 0.983607 | 0.992333 | 0.998953 | 0.978925 | 0.979358 | 0.979078 | 0.0661003 |
| recall | 0.984565 | 0.965429 | 0.969388 | 0.987654 | 0.990705 | 0.972491 | 0.978925 | 0.978372 | 0.978925 | 0.0661003 |
| f1-score | 0.974277 | 0.964811 | 0.971122 | 0.985626 | 0.991518 | 0.985545 | 0.978925 | 0.978817 | 0.978948 | 0.0661003 |
| support | 2462 | 1562 | 1960 | 1944 | 1829 | 1963 | 0.978925 | 11720 | 11720 | 0.0661003 |
Confusion matrix
| Predicted as 0 | Predicted as 1 | Predicted as 2 | Predicted as 3 | Predicted as 4 | Predicted as 5 | |
|---|---|---|---|---|---|---|
| Labeled as 0 | 2424 | 7 | 5 | 25 | 0 | 1 |
| Labeled as 1 | 2 | 1508 | 47 | 0 | 5 | 0 |
| Labeled as 2 | 9 | 47 | 1900 | 1 | 3 | 0 |
| Labeled as 3 | 19 | 2 | 0 | 1920 | 3 | 0 |
| Labeled as 4 | 9 | 0 | 1 | 6 | 1812 | 1 |
| Labeled as 5 | 51 | 0 | 0 | 0 | 3 | 1909 |
Learning curves
Permutation-based Importance
Confusion Matrix
Normalized Confusion Matrix
ROC Curve
Precision Recall Curve
