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AutoML Performance Boxplot

Features Importance

Spearman Correlation of Models

Summary of Ensemble
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Ensemble structure
| Model |
Weight |
| 3_Linear |
1 |
| 6_Default_RandomForest |
1 |
Metric details:
| Metric |
Score |
| MAE |
47.0012 |
| MSE |
3182.24 |
| RMSE |
56.4114 |
| R2 |
0.485003 |
| MAPE |
0.346827 |
Learning curves

True vs Predicted

Predicted vs Residuals

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Summary of 6_Default_RandomForest
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Random Forest
- n_jobs: -1
- criterion: squared_error
- max_features: 0.9
- min_samples_split: 30
- max_depth: 4
- eval_metric_name: rmse
- explain_level: 2
Validation
- validation_type: split
- train_ratio: 0.75
- shuffle: True
Optimized metric
rmse
Training time
2.1 seconds
Metric details:
| Metric |
Score |
| MAE |
48.7839 |
| MSE |
3373.91 |
| RMSE |
58.0854 |
| R2 |
0.453984 |
| MAPE |
0.369451 |
Learning curves

Permutation-based Importance

True vs Predicted

Predicted vs Residuals

SHAP Importance

SHAP Dependence plots
Dependence (Fold 1)

SHAP Decision plots
Top-10 Worst decisions (Fold 1)

Top-10 Best decisions (Fold 1)

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Summary of 2_DecisionTree
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Decision Tree
- n_jobs: -1
- criterion: squared_error
- max_depth: 3
- explain_level: 2
Validation
- validation_type: split
- train_ratio: 0.75
- shuffle: True
Optimized metric
rmse
Training time
3.0 seconds
Metric details:
| Metric |
Score |
| MAE |
54.178 |
| MSE |
4309.89 |
| RMSE |
65.6498 |
| R2 |
0.30251 |
| MAPE |
0.418572 |
Learning curves

Permutation-based Importance

True vs Predicted

Predicted vs Residuals

SHAP Importance

SHAP Dependence plots
Dependence (Fold 1)

SHAP Decision plots
Top-10 Worst decisions (Fold 1)

Top-10 Best decisions (Fold 1)

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Summary of 3_Linear
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Linear Regression (Linear)
- n_jobs: -1
- explain_level: 2
Validation
- validation_type: split
- train_ratio: 0.75
- shuffle: True
Optimized metric
rmse
Training time
2.1 seconds
Metric details:
| Metric |
Score |
| MAE |
46.7478 |
| MSE |
3324.55 |
| RMSE |
57.6589 |
| R2 |
0.461973 |
| MAPE |
0.342732 |
Learning curves

Coefficients
| feature |
Learner_1 |
| s5 |
8.55746 |
| bmi |
6.04881 |
| bp |
5.10877 |
| s2 |
3.32554 |
| s4 |
1.1412 |
| intercept |
-0.0358182 |
| s6 |
-0.32707 |
| age |
-0.335406 |
| s3 |
-1.43409 |
| sex |
-3.44143 |
| s1 |
-5.06768 |
Permutation-based Importance

True vs Predicted

Predicted vs Residuals

SHAP Importance

SHAP Dependence plots
Dependence (Fold 1)

SHAP Decision plots
Top-10 Worst decisions (Fold 1)

Top-10 Best decisions (Fold 1)

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Summary of 1_Baseline
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Baseline Regressor (Baseline)
- n_jobs: -1
- explain_level: 2
Validation
- validation_type: split
- train_ratio: 0.75
- shuffle: True
Optimized metric
rmse
Training time
0.1 seconds
Metric details:
| Metric |
Score |
| MAE |
67.0125 |
| MSE |
6186.65 |
| RMSE |
78.6553 |
| R2 |
-0.00121404 |
| MAPE |
0.59179 |
Learning curves

True vs Predicted

Predicted vs Residuals

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Summary of 5_Default_NeuralNetwork
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Neural Network
- n_jobs: -1
- dense_1_size: 32
- dense_2_size: 16
- learning_rate: 0.05
- explain_level: 2
Validation
- validation_type: split
- train_ratio: 0.75
- shuffle: True
Optimized metric
rmse
Training time
1.4 seconds
Metric details:
| Metric |
Score |
| MAE |
53.2572 |
| MSE |
4228.82 |
| RMSE |
65.0294 |
| R2 |
0.315631 |
| MAPE |
0.395675 |
Learning curves

Permutation-based Importance

True vs Predicted

Predicted vs Residuals

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Summary of 4_Default_Xgboost
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Extreme Gradient Boosting (Xgboost)
- n_jobs: -1
- objective: reg:squarederror
- eta: 0.075
- max_depth: 6
- min_child_weight: 1
- subsample: 1.0
- colsample_bytree: 1.0
- eval_metric: rmse
- explain_level: 2
Validation
- validation_type: split
- train_ratio: 0.75
- shuffle: True
Optimized metric
rmse
Training time
2.5 seconds
Metric details:
| Metric |
Score |
| MAE |
51.8944 |
| MSE |
3968.4 |
| RMSE |
62.9952 |
| R2 |
0.357776 |
| MAPE |
0.409052 |
Learning curves

Permutation-based Importance

True vs Predicted

Predicted vs Residuals

SHAP Importance

SHAP Dependence plots
Dependence (Fold 1)

SHAP Decision plots
Top-10 Worst decisions (Fold 1)

Top-10 Best decisions (Fold 1)

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