Coefficients of regression model:
{{ model_coef }}
You have to train model with parameter regularized_refit=False
{% endif %}Gini for training sample

Gini for test sample {{ n_test_sample }}

To calculate VIF you need more then one feature
{% endif %}Total PSI
{{ psi_total }}PSI for off-target events
{{ psi_zeros }}PSI for target events
{{ psi_ones }}Grouping by predictions on train sample (total)

Grouping by predictions target and off-target events on train sample

Grouping by predictions on test sample {{ n_test_sample }} (total)

Grouping by predictions target and off-target events on test sample {{ n_test_sample }}

PSI on grouped model predictions
| Total PSI | {{ psi_binned_total }} |
| PSI for off-target events | {{ psi_binned_zeros }} |
| PSI for target events | {{ psi_binned_ones }} |
To calculate PSI you need to call fit() and predict_proba() beforehand
{% endif %}

| ScoreBin | count | mean | std | min | 25% | 50% | 75% | max |
| {{ val[0] }} | {{ val[1] }} | {{ val[2] }} | {{ val[3] }} | {{ val[4] }} | {{ val[5] }} | {{ val[6] }} | {{ val[7] }} | {{ val[8] }} |

| Variable | Value | WOE | COEF | POINTS |
| {{ val[0] }} | {{ val[1] }} | {{ val[2] }} | {{ val[3] }} | {{ val[4] }} |
| Feature | |
| {{ val[0] }} | {{ val[1] }} |