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:
“I seek in books only to give myself pleasure by honest amusement; or if I study, I seek only the learning that treats of the knowledge of myself and instructs me in how to die well and live well.”
—Michel de Montaigne (1533–1592)
“If you think of learning as a path, you can picture yourself walking beside her rather than either pushing or dragging or carrying her along.”
—Polly Berrien Berends (20th century)
“Justice turns the scale, bringing to some learning through suffering.”
—Aeschylus (525–456 B.C.)