How to create Credit Card Fraud Detection model so that it captures dependency in the observations
Add another column(s) to your data which is "time since last transaction" and/or perhaps "number of transactions in the previous n mins". You could experiment on different values of n or even include multiple.
This seems like it would capture the information required? Hope that helps!
I want to create ML Model to identify if the Transaction is fraud or not.
Each row represents one Transaction. I understand that this ML Model can be built. What the model will be missing is the behaviour when Multiple Transactions are done within short duration. How do I capture that behaviour? If 1st transaction for a card happens at 10 am and other transaction happens at 10.01 am then that Transaction is generally Fraud. But my model is missing that. Please help