Model Explainer
Feature Importances
Classification Stats
Individual Predictions
Feature Dependence
Feature Importances
Feature Importances
Model performance metrics
metric
Score
accuracy
0.449
precision
0.0
recall
0.0
f1
0.0
roc_auc_score
0.5
pr_auc_score
0.551
log_loss
0.693
Confusion Matrix
How many false positives and false negatives?
Precision Plot
Does fraction positive increase with predicted probability?
Classification Plot
Distribution of labels above and below cutoff
ROC AUC Plot
Trade-off between False positives and false negatives
PR AUC Plot
Trade-off between Precision and Recall
Lift Curve
Performance how much better than random?
Cumulative Precision
Expected distribution for highest scores
Individual Predictions
Select Random Index
Selected index:
None
Prediction
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Contributions Plot
How has each feature contributed to the prediction?
no index selected
Partial Dependence Plot
Contributions Table
How has each feature contributed to the prediction?
no index selected
Feature Dependence
Shap Summary
Ordering features by shap value
Shap Dependence
Relationship between feature value and SHAP value