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package solver

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Type Members

  1. class BPSolver extends OneTimeProbabilisticBeliefPropagation
  2. class GibbsSolver extends BaseUnweightedSampler with ProbabilisticGibbs with OneTime
  3. type Solution = (List[Factor[Double]], Map[Variable[_], Factor[_]])

    A solution consists of the eliminated factors over globals, and the map of recording factors.

  4. type Solver = (Problem, Set[Variable[_]], Set[Variable[_]], List[Factor[Double]]) ⇒ Solution

    A Solver takes a set of variables to eliminate, a set of variables to preserve, and a list of factors.

    A Solver takes a set of variables to eliminate, a set of variables to preserve, and a list of factors. It returns a list of factors that mention only the preserved variables.

  5. class VESolver extends VariableElimination[Double]

Value Members

  1. def marginalBeliefPropagation(iterations: Int = 100)(problem: Problem, toEliminate: Set[Variable[_]], toPreserve: Set[Variable[_]], factors: List[Factor[Double]]): Solution

    Creates a belief propagation solver.

    Creates a belief propagation solver.

    iterations

    number of iterations of BP to run

    problem

    the problem to solve

    toEliminate

    the variables to be eliminated

    toPreserve

    the variables to be preserved (not eliminated)

    factors

    all the factors in the problem

  2. def marginalGibbs(numSamples: Int, burnIn: Int, interval: Int, blockToSampler: BlockSamplerCreator)(problem: Problem, toEliminate: Set[Variable[_]], toPreserve: Set[Variable[_]], factors: List[Factor[Double]]): Solution

    Creates a Gibbs sampling solver.

    Creates a Gibbs sampling solver.

    numSamples

    number of samples to take

    burnIn

    number of burn-in samples to throw away

    interval

    number of samples to throw away between recorded samples

    blockToSampler

    function for creating Gibbs block samplers

    problem

    the problem to solve

    toEliminate

    the variables to be eliminated

    toPreserve

    the variables to be preserved (not eliminated)

    factors

    all the factors in the problem

  3. def marginalVariableElimination(problem: Problem, toEliminate: Set[Variable[_]], toPreserve: Set[Variable[_]], factors: List[Factor[Double]]): Solution

    Creates a variable elimination solver.

    Creates a variable elimination solver.

    problem

    the problem to solve

    toEliminate

    the variables to be eliminated

    toPreserve

    the variables to be preserved (not eliminated)

    factors

    all the factors in the problem

  4. def mpeBeliefPropagation(iterations: Int = 100)(problem: Problem, toEliminate: Set[Variable[_]], toPreserve: Set[Variable[_]], factors: List[Factor[Double]]): Solution

    Creates an MPE belief propagation solver.

    Creates an MPE belief propagation solver.

    iterations

    number of iterations of BP to run

    problem

    the problem to solve

    toEliminate

    the variables to be eliminated

    toPreserve

    the variables to be preserved (not eliminated)

    factors

    all the factors in the problem

  5. def mpeVariableElimination(problem: Problem, toEliminate: Set[Variable[_]], toPreserve: Set[Variable[_]], factors: List[Factor[Double]]): Solution

    Creates an MPE variable elimination solver.

    Creates an MPE variable elimination solver.

    problem

    the problem to solve

    toEliminate

    the variables to be eliminated

    toPreserve

    the variables to be preserved (not eliminated)

    factors

    all the factors in the problem

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