Confusion regarding Hidden Markov Model and Conditional Random Fields

I am a bit confused about Hidden Markov Models and Conditional Random Fields. I wanna know id they are supervised开发者_高级运维 or un-supervised learning methods? Thanks

Well as I read several papers, they are both supervised methods and they need a labeled training set to be trained on.

Neither. They're models for the underlying representation of knowledge. What happens during training is that certain transitions, being reinforced, become higher probability.