I have below two queries, Can you please help me in that -
When working on Churn prediction/credit risk, there are quite few defaulters which cause imbalance in dataset. I know couple of methods to fix this like loss matrix, additional weight to less occurring outcome. But can we decide how much weight we need to give. For e.g. If I give 0.7 to non-default and 0.3 to defaulters. How can I decide these weightage
In some scenarios, one variables have different scale (10,000 - 1,000,000) and others have different(1-10). How can we normalize it. Can you please let us know different methods (log function) also please confirm if we use z-score for same purpose
Thanks in advance!