Summary of 4_Default_Xgboost

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Extreme Gradient Boosting (Xgboost)

Validation

Optimized metric

logloss

Training time

17.3 seconds

Metric details

C1 C2 C3 C4 C5 nan accuracy macro avg weighted avg logloss
precision 0.906977 0.935897 1 0.833333 1 0.833333 0.922535 0.918257 0.925334 0.269899
recall 0.906977 0.948052 0.571429 1 1 1 0.922535 0.90441 0.922535 0.269899
f1-score 0.906977 0.941935 0.727273 0.909091 1 0.909091 0.922535 0.899061 0.920499 0.269899
support 43 77 7 5 5 5 0.922535 142 142 0.269899

Confusion matrix

Predicted as C1 Predicted as C2 Predicted as C3 Predicted as C4 Predicted as C5 Predicted as nan
Labeled as C1 39 4 0 0 0 0
Labeled as C2 4 73 0 0 0 0
Labeled as C3 0 1 4 1 0 1
Labeled as C4 0 0 0 5 0 0
Labeled as C5 0 0 0 0 5 0
Labeled as nan 0 0 0 0 0 5

Learning curves

Learning curves

Permutation-based Importance

Permutation-based Importance

SHAP Importance

SHAP Importance

SHAP Dependence plots

Dependence C1 (Fold 1)

SHAP Dependence from fold 1

Dependence C2 (Fold 1)

SHAP Dependence from fold 1

Dependence C3 (Fold 1)

SHAP Dependence from fold 1

Dependence C4 (Fold 1)

SHAP Dependence from fold 1

Dependence C5 (Fold 1)

SHAP Dependence from fold 1

Dependence nan (Fold 1)

SHAP Dependence from fold 1

SHAP Decision plots

Worst decisions for selected sample 1 (Fold 1)

SHAP worst decisions from Fold 1

Worst decisions for selected sample 2 (Fold 1)

SHAP worst decisions from Fold 1

Worst decisions for selected sample 3 (Fold 1)

SHAP worst decisions from Fold 1

Worst decisions for selected sample 4 (Fold 1)

SHAP worst decisions from Fold 1

Best decisions for selected sample 1 (Fold 1)

SHAP best decisions from Fold 1

Best decisions for selected sample 2 (Fold 1)

SHAP best decisions from Fold 1

Best decisions for selected sample 3 (Fold 1)

SHAP best decisions from Fold 1

Best decisions for selected sample 4 (Fold 1)

SHAP best decisions from Fold 1

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