Summary of 4_Default_Xgboost_categorical_mix

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Extreme Gradient Boosting (Xgboost)

Validation

Optimized metric

logloss

Training time

28.6 seconds

Metric details

C1 C2 C3 C4 C5 nan accuracy macro avg weighted avg logloss
precision 0.909091 0.935065 0.5 0.714286 1 1 0.908451 0.843074 0.902552 0.320313
recall 0.930233 0.935065 0.285714 1 1 1 0.908451 0.858502 0.908451 0.320313
f1-score 0.91954 0.935065 0.363636 0.833333 1 1 0.908451 0.841929 0.903186 0.320313
support 43 77 7 5 5 5 0.908451 142 142 0.320313

Confusion matrix

Predicted as C1 Predicted as C2 Predicted as C3 Predicted as C4 Predicted as C5 Predicted as nan
Labeled as C1 40 3 0 0 0 0
Labeled as C2 3 72 2 0 0 0
Labeled as C3 1 2 2 2 0 0
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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