Statements (18)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:algorithm
|
| gptkbp:advantage |
faster convergence for large data
may have higher variance in estimates |
| gptkbp:appliesTo |
gptkb:machine_learning
statistics |
| gptkbp:feature |
can handle incomplete data
improves scalability for large datasets uses random samples in E-step |
| gptkbp:fullName |
stochastic Expectation-Maximization
|
| https://www.w3.org/2000/01/rdf-schema#label |
stochastic EM
|
| gptkbp:proposedBy |
Celeux and Diebolt
|
| gptkbp:relatedTo |
gptkb:Expectation-Maximization_algorithm
stochastic approximation |
| gptkbp:usedFor |
parameter estimation
latent variable models |
| gptkbp:yearProposed |
1985
|
| gptkbp:bfsParent |
gptkb:expectation-maximization_algorithm
|
| gptkbp:bfsLayer |
7
|