package marginalmap

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  1. trait AnytimeMarginalMAP extends MarginalMAPAlgorithm with Anytime

    Anytime algorithms that compute most likely values of some elements, and marginalize over all other elements.

    Anytime algorithms that compute most likely values of some elements, and marginalize over all other elements. A class that implements this trait must implement initialize, runStep, and computeMostLikelyValue methods.

  2. class AnytimeProbEvidenceMarginalMAP extends ProbEvidenceMarginalMAP with AnytimeSampler with AnytimeMarginalMAP
  3. trait AnytimeStructuredMarginalMAP extends StructuredMarginalMAPAlgorithm with AnytimeStructured with AnytimeMarginalMAP
  4. trait DecompositionMarginalMAP extends StructuredMarginalMAPAlgorithm with OneTimeStructuredMarginalMAP with DecompositionStructuredAlgorithm
  5. trait MarginalMAPAlgorithm extends Algorithm

    Algorithms that compute max a posteriori (MAP) values of some elements, and marginalize over all other elements.

  6. abstract class MarginalMAPBeliefPropagation extends MarginalMAPAlgorithm with ProbabilisticBeliefPropagation
  7. class MarginalMAPVEStrategy extends RaisingStrategy

    A solving strategy that uses MPE VE to solve non-nested problems, and performs the MAP step at the top level.

    A solving strategy that uses MPE VE to solve non-nested problems, and performs the MAP step at the top level. It is assumed that at the top level, "toPreserve" variables are the MAP variables.

  8. trait OneTimeMarginalMAP extends MarginalMAPAlgorithm with OneTime

    One-time algorithms that compute the most likely values of some elements, and marginalize over others.

    One-time algorithms that compute the most likely values of some elements, and marginalize over others. A class that implements this trait must implement run and computeMostLikelyValue methods.

  9. class OneTimeProbEvidenceMarginalMAP extends ProbEvidenceMarginalMAP with OneTimeSampler with OneTimeMarginalMAP
  10. trait OneTimeStructuredMarginalMAP extends StructuredMarginalMAPAlgorithm with OneTimeStructured with OneTimeMarginalMAP
  11. abstract class ProbEvidenceMarginalMAP extends MetropolisHastings with MarginalMAPAlgorithm

    An algorithm for marginal MAP.

    An algorithm for marginal MAP. This algorithm works by searching for the assignment to the MAP elements that maximizes the probability of evidence of observing that assignment. Uses one time probability of evidence sampling at each iteration for the given number of samples. Since the probability of evidence is just an estimate, this algorithm is allowed to repeatedly take more probability of evidence samples until it believes with high confidence that one state is better than another state, or it has reached the maximum number of allowed runs. The maximization is done by simulated annealing.

  12. abstract class StructuredMarginalMAPAlgorithm extends StructuredAlgorithm with MarginalMAPAlgorithm

    A structured marginal MAP algorithm.

  13. class StructuredMarginalMAPVE extends StructuredMarginalMAPAlgorithm with DecompositionMarginalMAP

    A structured marginal MAP algorithm that uses VE to compute MAP queries.

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