Question

Given a sequence of observations and a HMM model, which of the
2
following fundamental problems of HMM finds the most likely sequence of
states that produced the observations in an efficient way?
O Evaluation problem
Likelihood estimation problem
O Learning problem
O Decoding problem​

Answer 1

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Answer 2

Answer:

The problems which finds the most likely sequence of the states which produce observations in effective way are -

• Likelihood estimation problem
• Learning problem
• Decoding problem​

Explanation:

• Hidden Markov Models (HMM) describe a probabilistic graphical models that anticipate a sequence of unknown variables (hidden) from observed variables.
• HMM has a set of states each of which possesses a limited number of transitions and emissions.
• The transition between the states has an assigned probability.
• Each and every model starts from the start state and ends at the end state.
• The applications of HMM are -

1. Statistical mechanics
2. Economics
3. Bioinformatics
4. Signal processing
5. Pattern recognition etc.

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