Statements (24)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:algorithm
expectation-maximization algorithm |
| gptkbp:alsoKnownAs |
forward-backward algorithm (in context of HMM training)
|
| gptkbp:assumes |
gptkb:Markov_property
discrete or continuous observations |
| gptkbp:category |
unsupervised learning
|
| gptkbp:complexity |
O(N^2T)
|
| gptkbp:convergesTo |
local maximum of likelihood function
|
| gptkbp:field |
gptkb:machine_learning
statistics computational linguistics |
| gptkbp:firstPublished |
1970
|
| https://www.w3.org/2000/01/rdf-schema#label |
Baum-Welch Algorithm
|
| gptkbp:input |
observed sequence
initial HMM parameters |
| gptkbp:namedAfter |
gptkb:Lloyd_R._Welch
gptkb:Leonard_E._Baum |
| gptkbp:output |
maximum likelihood estimates of HMM parameters
|
| gptkbp:relatedTo |
Markov chain
forward-backward algorithm |
| gptkbp:usedFor |
parameter estimation
training hidden Markov models |
| gptkbp:bfsParent |
gptkb:Viterbi_Algorithm
|
| gptkbp:bfsLayer |
7
|