I have a dataset which has around 10K records.
My objective is to predict whether the customer will churn or not. Binary classification problem with each class representing around 55:45 proportion and 20 features.
I understand when it's just about prediction, I can apply some binary classification algorithm and find out whether the customer churns or not
But how do I incorporate the objective of finding whether the customer will churn in 30 days or not?
Another example is find whether patient will be dead within 30 days from the date of discharge. I have his date of discharge along with other features like Blood pressure, Cholesterol etc.
Rather than just predicting whether he will be dead or not anytime in future, I would like to restrict it to 30 days from date of discharge.
Hope I gave the details to help you understand the question better.