Training Version 1.0
Accuracy, Trigger Alert When:
Accuracy is below 0.6, Positive Class:
deniedloans that were identified by the model as
approvedleading to a chargeback/immediate financial loss for the company).
approvedloans that were classified as
deniedleading to an awkward moment at the register and an upset customer).
deny, misclassifying all transactions can still result in 95% model accuracy.
purpose) drifting, which likely means data drift is causing performance degradation. In addition to the baseline and current distributions diverging from each other, we also see the input
credit_cardin the feature
purposethat are only seen in the production data and not the baseline dataset. In this case, where the baseline is your training dataset, you should retrain your model with the new data.