Hidden Markov models u
3 important questions on Hidden Markov models u
What are the three basic problems for HMM?
- The Decoding Problem – what is the most probable path? Given a model and a sequence of observations, what is the most likely state sequence in the model that produced the observations?
- The Evaluation Problem – how likely is a given sequence? Given an HMM and a sequence of observations, what is the probability that the observations are generated by the model?
- The Learning Problem – how to set the HMM parameters? Given a model and a sequence of observations, how should we adjust the model parameters in order to maximize the generation of the (training) data
What is the solution to the decoding problem?
the Viterbi algorithm.
What is the solution to the learning problem?
the Forward-Backward (Baum-Welch) algorithm
The question on the page originate from the summary of the following study material:
- A unique study and practice tool
- Never study anything twice again
- Get the grades you hope for
- 100% sure, 100% understanding
Remember faster, study better. Scientifically proven.
