Hidden Markov Models - Distinct Observation Symbols

1. What is the observations in a hidden Markov model?
2. Are observations independent in HMM?
3. What are the 3 fundamental problems Markov models are characterized with?
4. What are the basic elements HMM?

What is the observations in a hidden Markov model?

Observation refers to the data we know and can observe. Markov process is shown by the interaction between “Rainy” and “Sunny” in the below diagram and each of these are HIDDEN STATES. OBSERVATIONS are known data and refers to “Walk”, “Shop”, and “Clean” in the above diagram.

Are observations independent in HMM?

In HMM, each observation is generated by some states and observations are independent of each other. Any HMM can be defined with five parameters i.e., ) where N is the number of hidden states.

What are the 3 fundamental problems Markov models are characterized with?

HMM provides solution of three problems : evaluation, decoding and learning to find most likelihood classification.

What are the basic elements HMM?

An HMM consists of two stochastic processes, namely, an invisible process of hidden states and a visible process of observable symbols. The hidden states form a Markov chain, and the probability distribution of the observed symbol depends on the underlying state.