Summary of 6_Default_RandomForest

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Random Forest

Validation

Optimized metric

logloss

Training time

9.9 seconds

Metric details

0 1 2 3 4 accuracy macro avg weighted avg logloss
precision 0.878049 0.3875 0.9375 0.392857 0.5 0.56 0.619181 0.621074 0.860851
recall 0.765957 0.62 0.517241 0.323529 0.333333 0.56 0.512012 0.56 0.860851
f1-score 0.818182 0.476923 0.666667 0.354839 0.4 0.56 0.543322 0.569706 0.860851
support 47 50 29 34 15 0.56 175 175 0.860851

Confusion matrix

Predicted as 0 Predicted as 1 Predicted as 2 Predicted as 3 Predicted as 4
Labeled as 0 36 5 0 6 0
Labeled as 1 2 31 1 11 5
Labeled as 2 1 13 15 0 0
Labeled as 3 1 22 0 11 0
Labeled as 4 1 9 0 0 5

Learning curves

Learning curves

Permutation-based Importance

Permutation-based Importance

SHAP Importance

SHAP Importance

SHAP Dependence plots

Dependence 0 (Fold 1)

SHAP Dependence from fold 1

Dependence 1 (Fold 1)

SHAP Dependence from fold 1

Dependence 2 (Fold 1)

SHAP Dependence from fold 1

Dependence 3 (Fold 1)

SHAP Dependence from fold 1

Dependence 4 (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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