Support for performing inference on certain variables and storing the results of inference. Inferencer can be requested to perform inference on certain variables. For example, BPInferencer and SamplingInferencer. MCMCSampling-based inference. Sampler, with sampling requests optionally guided by an arbitrary "context". SettingsSampler considers an arbitrary number of value settings of a portion of the possible world. ProposalSampler represents these changes to the current possible world as aProposal object, and selects a Proposal according to its associated change in score. VariableSettingsSampler is a SettingsSampler in which the proposals are all possible settings of a given variable. MHSampler is a SettingsSampler in which one proposal is a noop and the other is defined by a (possibly user-defined) proposal function. Belief PropagationMarginal Inference (Sum Product)Loopy BPval summary = new BPSummary(variables, model)
BP.inferLoopy(summary, iterations)
Forward-Backwardval summary = BP.inferChainSum(chains, model)
Map Inference (Max Product) |