learning

Type Members

1. class ExpectationMaximization extends Algorithm with ParameterLearner

   

   Expectation maximization iteratively produces an estimate of sufficient statistics for learnable parameters, then maximizes the parameters according to the estimate.

   Expectation maximization iteratively produces an estimate of sufficient statistics for learnable parameters, then maximizes the parameters according to the estimate. It uses an factored inference algorithm, SufficientStatisticsVariableElimination, to produce the estimate of the sufficient statistics. This class can be extended with a different expectation or maximization algorithm; see the code for details.

2. class SufficientStatisticsFactor extends AnyRef

   

   Methods for creating probabilistic factors associated with elements and their sufficient statistics.