I am working on a binary classification task with a pretty straightforward input set of numeric features. One of these features is particularly good, but it cannot be used in real life because it's a measure that is obtained after the fact has occurred. Is it possible to predict this measure based on the other features, and then build a model including this predicted measure?
In more detail, I am building a classifier for this challenge from the UCI repo: https://archive.ics.uci.edu/ml/datasets/bank+marketing
The feature that cannot be used is the call duration because one can't know how long a call will last before it takes place. So I am wondering, could I build a regression model or at least a binned classifier to predict how long a call will last before it takes place, then feed this prediction to the model and replace the provided call duration feature?