public final class OnlineLearning extends Object
|Constructor and Description|
Initializes a new instance of the
|Modifier and Type||Method and Description|
Adapt the parameters of a Bayesian network using Bayesian statistics.
Gets the evidence used internally.
public OnlineLearning(Network network, InferenceFactory factory)
OnlineLearningclass. Learning uses inference as a subroutine, and creates one or more inference engines via the [factory] parameter.
network- The network whose parameters are being adapted.
factory- The inference factory used to create inference engines in cases when learning requires inference.
public Evidence getEvidence()
public void adapt(Evidence evidence, OnlineLearningOptions options) throws InconsistentEvidenceException
For nodes to be adapted, they must have Experience tables assigned (and optionally fading tables).
In the case a discrete node, the experience table combined with the probability are used to create a Dirichlet distribution. This distribution acts as a prior during the Bayesian inference process.
evidence- The evidence to learn.
options- Options that affect how parameters are adapted.
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