Uses of Class
cc.mallet.grmm.types.FactorGraph

Packages that use FactorGraph

cc.mallet.grmm.inference
cc.mallet.grmm.inference.gbp
cc.mallet.grmm.learning
cc.mallet.grmm.types
cc.mallet.grmm.util

Uses of FactorGraph in cc.mallet.grmm.inference

Fields in cc.mallet.grmm.inference declared as FactorGraph

protected FactorGraph

AbstractBeliefPropagation.mdlCurrent

Methods in cc.mallet.grmm.inference that return FactorGraph

static FactorGraph	RandomGraphs.createGridWithObs(RandomGraphs.FactorGenerator gridGener, RandomGraphs.FactorGenerator obsGener, int size)
static FactorGraph	RandomGraphs.createRandomChain(Randoms r, int length)
static FactorGraph	RandomGraphs.createUniformChain(int length)
static FactorGraph	RandomGraphs.createUniformGrid(int length)

Methods in cc.mallet.grmm.inference with parameters of type FactorGraph

static void	RandomGraphs.addRandomNodePotentials(java.util.Random r, FactorGraph mdl)
static double[]	Utils.allL1MarginalDistance(FactorGraph mdl, Inferencer inf1, Inferencer inf2)
static double	Utils.avgL1MarginalDistance(FactorGraph mdl, Inferencer inf1, Inferencer inf2)
JunctionTree	JunctionTreeInferencer.buildJunctionTree(FactorGraph mdl) Constructs a junction tree from a given factor graph.
void	VariableElimination.computeMarginals(FactorGraph m)
void	TRP.computeMarginals(FactorGraph m)
void	TreeBP.computeMarginals(FactorGraph fg)
void	SamplingInferencer.computeMarginals(FactorGraph mdl)
void	ResidualBP.computeMarginals(FactorGraph mdl)
void	LoopyBP.computeMarginals(FactorGraph mdl)
void	JunctionTreeInferencer.computeMarginals(FactorGraph mdl)
void	Inferencer.computeMarginals(FactorGraph mdl) Computes marginal distributions for a factor graph.
void	BruteForceInferencer.computeMarginals(FactorGraph mdl)
abstract void	AbstractInferencer.computeMarginals(FactorGraph fg)
double	VariableElimination.computeNormalizationFactor(FactorGraph m) Computes the normalization constant for a model.
protected void	AbstractBeliefPropagation.doneWithGraph(FactorGraph mdl)
protected void	TRP.initForGraph(FactorGraph m)
protected void	TreeBP.initForGraph(FactorGraph fg)
protected void	AbstractBeliefPropagation.initForGraph(FactorGraph mdl)
Factor	BruteForceInferencer.joint(FactorGraph model)
static double	Utils.lookupMinusLogZ(FactorGraph mdl, Inferencer inf) Returns ths value of -log Z in mdl according to the given inferencer.
static TRP.TreeListFactory	TRP.TreeListFactory.makeFromReaders(FactorGraph fg, java.util.List readerList)
static double	Utils.maxL1MarginalDistance(FactorGraph mdl, Inferencer inf1, Inferencer inf2)
Tree	TRP.TreeFactory.nextTree(FactorGraph mdl)
Tree	TRP.AlmostRandomTreeFactory.nextTree(FactorGraph fullGraph)
Tree	TRP.TreeListFactory.nextTree(FactorGraph mdl)
double	Inferencer.query(FactorGraph mdl, Assignment assn) Computes the marginal probability of a given assignment to a small number of model variables.
double	AbstractInferencer.query(FactorGraph mdl, Assignment assn)
static TRP.TreeListFactory	TRP.TreeListFactory.readFromFiles(FactorGraph fg, java.util.List fileList)
Assignment	Sampler.sample(FactorGraph mdl, int N) Samples from the distribution of a given undirected model.
Assignment	GibbsSampler.sample(FactorGraph mdl, int N)
Assignment	ExactSampler.sample(FactorGraph mdl, int N)
protected void	AbstractBeliefPropagation.sendMessage(FactorGraph mdl, Factor from, Variable to)
void	AbstractBeliefPropagation.MessageStrategy.sendMessage(FactorGraph mdl, Factor from, Variable to)
void	AbstractBeliefPropagation.SumProductMessageStrategy.sendMessage(FactorGraph mdl, Factor from, Variable to)
void	AbstractBeliefPropagation.MaxProductMessageStrategy.sendMessage(FactorGraph mdl, Factor from, Variable to)
protected void	AbstractBeliefPropagation.sendMessage(FactorGraph mdl, Variable from, Factor to)
void	AbstractBeliefPropagation.MessageStrategy.sendMessage(FactorGraph mdl, Variable from, Factor to)
void	AbstractBeliefPropagation.SumProductMessageStrategy.sendMessage(FactorGraph mdl, Variable from, Factor to)
void	AbstractBeliefPropagation.MaxProductMessageStrategy.sendMessage(FactorGraph mdl, Variable from, Factor to)
Factor	VariableElimination.unnormalizedMarginal(FactorGraph model, Variable query) The bulk of the variable-elimination algorithm.

Constructors in cc.mallet.grmm.inference with parameters of type FactorGraph

MessageArray(FactorGraph fg)

Uses of FactorGraph in cc.mallet.grmm.inference.gbp

Methods in cc.mallet.grmm.inference.gbp with parameters of type FactorGraph

static void	ClusterVariationalRegionGenerator.addAllFactors(FactorGraph mdl, java.util.List regions)
java.util.List	ClusterVariationalRegionGenerator.BaseRegionComputer.computeBaseRegions(FactorGraph mdl) Returns a list of top-level regions for use in the cluster variational method.
java.util.List	ClusterVariationalRegionGenerator.ByFactorRegionComputer.computeBaseRegions(FactorGraph mdl)
java.util.List	ClusterVariationalRegionGenerator.Grid2x2RegionComputer.computeBaseRegions(FactorGraph mdl)
void	ParentChildGBP.computeMarginals(FactorGraph mdl)
cc.mallet.grmm.inference.gbp.RegionGraph	RegionGraphGenerator.constructRegionGraph(FactorGraph mdl) Construct a region graph from an artbitrary model.
cc.mallet.grmm.inference.gbp.RegionGraph	Kikuchi4SquareRegionGenerator.constructRegionGraph(FactorGraph mdl)
cc.mallet.grmm.inference.gbp.RegionGraph	ClusterVariationalRegionGenerator.constructRegionGraph(FactorGraph mdl)
cc.mallet.grmm.inference.gbp.RegionGraph	BPRegionGenerator.constructRegionGraph(FactorGraph mdl)

Uses of FactorGraph in cc.mallet.grmm.learning

Subclasses of FactorGraph in cc.mallet.grmm.learning

static class

ACRF.UnrolledGraph

Uses of FactorGraph in cc.mallet.grmm.types

Subclasses of FactorGraph in cc.mallet.grmm.types

class	DirectedModel Class for directed graphical models.
class	UndirectedGrid A grid-shaped undirected graphical model.
class	UndirectedModel Class for pairwise undirected graphical models, also known as pairwise Markov random fields.

Constructors in cc.mallet.grmm.types with parameters of type FactorGraph

Assignment(FactorGraph mdl, int[] outcomes)
Creates an assignment over all Variables in a model.

Uses of FactorGraph in cc.mallet.grmm.util

Methods in cc.mallet.grmm.util that return FactorGraph

static FactorGraph	Models.addEvidence(FactorGraph mdl, Assignment assn) Returns a new factor graph, the same as a given one, except that all the nodes in the given Assignment are clamped as evidence.
static FactorGraph	Models.addEvidence(FactorGraph mdl, Assignment assn, java.util.Map toSlicedMap)
FactorGraph	ModelReader.readModel(java.io.BufferedReader in)

Methods in cc.mallet.grmm.util with parameters of type FactorGraph

static FactorGraph	Models.addEvidence(FactorGraph mdl, Assignment assn) Returns a new factor graph, the same as a given one, except that all the nodes in the given Assignment are clamped as evidence.
static FactorGraph	Models.addEvidence(FactorGraph mdl, Assignment assn, java.util.Map toSlicedMap)
static Assignment	Models.bestAssignment(FactorGraph mdl, Inferencer inf) Returns the highest-score Assignment in a model according to a given inferencer.
static double	Models.entropy(FactorGraph mdl) Computes the exact entropy of a factor graph distribution using the junction tree algorithm.
static double	Models.KL(FactorGraph mdl1, FactorGraph mdl2) Computes the KL divergence KL(mdl1||mdl2).
static org._3pq.jgrapht.UndirectedGraph	Graphs.mdlToGraph(FactorGraph fg) Converts a FactorGraph into a plain graph where each Variable is a vertex, and two Variables are connected by an edge if they are arguments to the same factor.
static void	Models.removeConstantFactors(FactorGraph sliced)
static void	ModelWriter.writeModel(FactorGraph fg, java.io.Writer w)