Summary of Ensemble
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Ensemble structure
| Model |
Weight |
| 2_DecisionTree |
1 |
| 4_Default_Xgboost |
2 |
| 5_Default_NeuralNetwork |
1 |
| 6_Default_RandomForest |
1 |
Metric details
|
0 |
1 |
2 |
3 |
4 |
accuracy |
macro avg |
weighted avg |
logloss |
| precision |
0.904762 |
0.48 |
0.607143 |
0.459459 |
0.555556 |
0.605714 |
0.601384 |
0.617634 |
0.758586 |
| recall |
0.808511 |
0.48 |
0.586207 |
0.5 |
0.666667 |
0.605714 |
0.608277 |
0.605714 |
0.758586 |
| f1-score |
0.853933 |
0.48 |
0.596491 |
0.478873 |
0.606061 |
0.605714 |
0.603072 |
0.610318 |
0.758586 |
| support |
47 |
50 |
29 |
34 |
15 |
0.605714 |
175 |
175 |
0.758586 |
Confusion matrix
|
Predicted as 0 |
Predicted as 1 |
Predicted as 2 |
Predicted as 3 |
Predicted as 4 |
| Labeled as 0 |
38 |
4 |
0 |
5 |
0 |
| Labeled as 1 |
0 |
24 |
3 |
15 |
8 |
| Labeled as 2 |
3 |
9 |
17 |
0 |
0 |
| Labeled as 3 |
0 |
9 |
8 |
17 |
0 |
| Labeled as 4 |
1 |
4 |
0 |
0 |
10 |
Learning curves
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