I have just gotten my feet wet with Hidden Markov Models. Now I want to apply them to tell whether a transaction from an ATM is suspicious or not. I have great confusion in defining my Hidden States.My attempt: A transaction is either suspicious or non-suspicious. Since I cannot tell, (this is hidden to me), whether a transaction is suspicious or not before analyzing it, therefore my Hidden States(Suspicious, Non-Suspicious). Does this hold? My great confusion: When I read about Hidden Markov Models on Weather example, I understood it this way: weather can be rainy or sunny - I mean its the 'same' weather that is switching between the two states. In my transaction case - one transaction cannot switch between being suspicious and non-suspicious. So, does my hidden states hold?Questions: Does my hidden states hold? Can I apply the HMM that way? Please advice, thanks.P.S: I had my Observations as location, time and amount of money but as of now I want clarification on Hidden states.
Can I apply Hidden Markov Models this way?
machine learning;markov process