Summary of 3_Linear
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Logistic Regression (Linear)
- num_class: 5
- explain_level: 2
Validation
- validation_type: split
- train_ratio: 0.75
- shuffle: True
- stratify: True
Optimized metric
logloss
Training time
8.2 seconds
Metric details
|
0 |
1 |
2 |
3 |
4 |
accuracy |
macro avg |
weighted avg |
logloss |
precision |
0.520548 |
0.333333 |
0.666667 |
0.380952 |
0.666667 |
0.491429 |
0.513633 |
0.476675 |
1.08111 |
recall |
0.808511 |
0.28 |
0.689655 |
0.235294 |
0.4 |
0.491429 |
0.482692 |
0.491429 |
1.08111 |
f1-score |
0.633333 |
0.304348 |
0.677966 |
0.290909 |
0.5 |
0.491429 |
0.481311 |
0.468777 |
1.08111 |
support |
47 |
50 |
29 |
34 |
15 |
0.491429 |
175 |
175 |
1.08111 |
Confusion matrix
|
Predicted as 0 |
Predicted as 1 |
Predicted as 2 |
Predicted as 3 |
Predicted as 4 |
Labeled as 0 |
38 |
7 |
0 |
2 |
0 |
Labeled as 1 |
19 |
14 |
3 |
11 |
3 |
Labeled as 2 |
5 |
4 |
20 |
0 |
0 |
Labeled as 3 |
6 |
13 |
7 |
8 |
0 |
Labeled as 4 |
5 |
4 |
0 |
0 |
6 |
Learning curves
Coefficients
Coefficients learner #1
|
0 |
1 |
2 |
3 |
4 |
intercept |
1.80784 |
2.01673 |
-2.72552 |
0.50835 |
-1.6074 |
nom_com |
0.380576 |
0.367239 |
-1.3283 |
-0.316997 |
0.897483 |
insee_com |
0.380576 |
0.367239 |
-1.3283 |
-0.316997 |
0.897483 |
nom_station |
0.0596358 |
0.0612581 |
-0.394172 |
-0.690075 |
0.963353 |
code_station |
-0.432223 |
-0.38998 |
1.4818 |
-0.231621 |
-0.427975 |
typologie |
0.29101 |
0.287097 |
-0.82773 |
0.215953 |
0.0336699 |
influence |
0.117335 |
0.103726 |
-0.347627 |
0.27383 |
-0.147263 |
valeur |
-0.853461 |
-0.0459299 |
1.04733 |
-0.125223 |
-0.0227164 |
lat |
0.225976 |
0.192929 |
-0.939005 |
-0.17667 |
0.69677 |
long |
-0.227332 |
-0.211188 |
0.572259 |
-0.642842 |
0.509103 |
jour_semaine_debut |
-0.0166062 |
-0.0175814 |
0.012963 |
0.0134262 |
0.00779841 |
jour_semaine_fin |
-0.0166062 |
-0.0175814 |
0.012963 |
0.0134262 |
0.00779841 |
jour_debut |
-0.0166062 |
-0.0175814 |
0.012963 |
0.0134262 |
0.00779841 |
jour_fin |
-0.0166062 |
-0.0175814 |
0.012963 |
0.0134262 |
0.00779841 |
heure_debut |
-0.00304425 |
-0.0303952 |
0.034434 |
-0.00822246 |
0.00722798 |
heure_fin |
-0.00304425 |
-0.0303952 |
0.034434 |
-0.00822246 |
0.00722798 |
Permutation-based Importance
SHAP Importance
SHAP Dependence plots
Dependence 0 (Fold 1)
Dependence 1 (Fold 1)
Dependence 2 (Fold 1)
Dependence 3 (Fold 1)
Dependence 4 (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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