Class | Description |
---|---|
ExpectationMaximization |
Abstract superclass for implementations of the expectation-maximization
algorithm for learning with latent variables.
|
HardEM |
EM algorithm which fits a point distribution to the single most probable
assignment of truth values to the latent variables during the E-step.
|
PairedDualLearner |
Learns the parameters of a HL-MRF with latent variables, using a maximum-likelihood
technique that interleaves updates of the parameters and inference steps for
fast training.
|
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