Summary of 3_Linear
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Logistic Regression (Linear)
- num_class: 4
- explain_level: 2
Validation
- validation_type: split
- train_ratio: 0.75
- shuffle: True
- stratify: True
Optimized metric
logloss
Training time
7.8 seconds
Metric details
|
0 |
1 |
2 |
3 |
accuracy |
macro avg |
weighted avg |
logloss |
precision |
0 |
0 |
0.618321 |
0.630389 |
0.623658 |
0.312177 |
0.589272 |
0.801042 |
recall |
0 |
0 |
0.694631 |
0.622571 |
0.623658 |
0.329301 |
0.623658 |
0.801042 |
f1-score |
0 |
0 |
0.654258 |
0.626456 |
0.623658 |
0.320179 |
0.605353 |
0.801042 |
support |
282 |
19 |
2682 |
2419 |
0.623658 |
5402 |
5402 |
0.801042 |
Confusion matrix
|
Predicted as 0 |
Predicted as 1 |
Predicted as 2 |
Predicted as 3 |
Labeled as 0 |
0 |
0 |
222 |
60 |
Labeled as 1 |
0 |
0 |
15 |
4 |
Labeled as 2 |
0 |
0 |
1863 |
819 |
Labeled as 3 |
0 |
0 |
913 |
1506 |
Learning curves
Coefficients
Coefficients learner #1
|
0 |
1 |
2 |
3 |
intercept |
-0.446662 |
-3.34533 |
2.02469 |
1.7673 |
filtre |
-0.0888187 |
0.154754 |
-0.0178255 |
-0.0481096 |
latitude |
-0.0141252 |
-0.0735754 |
0.0444655 |
0.043235 |
longitude |
0.0300214 |
-0.0624727 |
0.0400118 |
-0.00756055 |
has_agrement |
-0.134032 |
-0.441637 |
0.126474 |
0.449195 |
dept |
-0.0291757 |
0.0783951 |
-0.0435639 |
-0.00565552 |
year |
0.254794 |
-0.0158806 |
-0.186856 |
-0.0520575 |
month |
0.282456 |
-0.071908 |
-0.101168 |
-0.10938 |
weekday |
-0.0993311 |
0.106422 |
-0.00852444 |
0.00143376 |
count_controls_dept |
-0.175346 |
-0.359413 |
0.243545 |
0.291214 |
score_controls_dept |
-0.232151 |
-0.375072 |
0.0273233 |
0.5799 |
count_controls_filtre |
0.0762235 |
0.049562 |
-0.0335539 |
-0.0922316 |
score_controls_filtre |
-0.261644 |
-0.427335 |
0.161154 |
0.527825 |
count_controls_activite |
-0.00271059 |
-0.75941 |
0.22235 |
0.539771 |
score_controls_activite |
-0.136814 |
-0.30772 |
0.0218038 |
0.42273 |
count_controls_wday |
-0.0903018 |
0.269135 |
-0.102005 |
-0.0768278 |
score_controls_wday |
-0.0495039 |
0.0616961 |
-0.0118467 |
-0.000345442 |
Permutation-based Importance
SHAP Importance
SHAP Dependence plots
Dependence 0 (Fold 1)
Dependence 1 (Fold 1)
Dependence 2 (Fold 1)
Dependence 3 (Fold 1)
SHAP Decision plots
Worst decisions for selected sample 1 (Fold 1)
Worst decisions for selected sample 2 (Fold 1)
Worst decisions for selected sample 3 (Fold 1)
Worst decisions for selected sample 4 (Fold 1)
Best decisions for selected sample 1 (Fold 1)
Best decisions for selected sample 2 (Fold 1)
Best decisions for selected sample 3 (Fold 1)
Best decisions for selected sample 4 (Fold 1)
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