I have a naive Bayes ML model that takes call attributes and predicts if the caller is going to abandon the call while they are on hold waiting to speak to an agent. The model lives in Databricks ML flow, I have it registered.
What I need to do is extract the exact calculations so I can make them myself during the call. Once the user hangs up, the prediction is useless. I want to predict whether the caller breaks the threshold of "likely to abandon" based on a running tally of the features and weights during the call.
Is there a way to extract the calculations being made in the model and make them myself? Because of the way our software is set up, the business owners do not want to import the whole model and make predictions every time a feature is updated. It would eat significantly less resources to just have a running tally and once that tally breaks a threshold, flag the call.
Asking AI, it seems like the calculations are obscured and it's not easy to extract them and make them myself, especially if using a naive bayes model.
