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# solver 

#### package solver

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### Type Members

1. class
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]])

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]])

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]])

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]])

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]])

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