Learning
The parameter learning task in HMMs is to find, given an output sequence or a set of such sequences, the best set of state transition and output probabilities. The task is usually to derive the maximum likelihood estimate of the parameters of the HMM given the set of output sequences. No tractable algorithm is known for solving this problem exactly, but a local maximum likelihood can be derived efficiently using the Baum–Welch algorithm or the Baldi–Chauvin algorithm. The Baum–Welch algorithm is a special case of the expectation-maximization algorithm.
Read more about this topic: Hidden Markov Model
Famous quotes containing the word learning:
“Paul, thou art beside thyself; much learning doth make thee mad.”
—Bible: New Testament Acts, 26:24.
Said by Festus, the Roman Procurator.
“What terrible questions we are learning to ask! The former men believed in magic, by which temples, cities, and men were swallowed up, and all trace of them gone. We are coming on the secret of a magic which sweeps out of men’s minds all vestige of theism and beliefs which they and their fathers held and were framed upon.”
—Ralph Waldo Emerson (1803–1882)