Uses of Class
tuffy.infer.MRF

Packages that use MRF

tuffy.ground.partition	Data structures and algorithms for MRF partitioning.
tuffy.helper	Misc functionalities to help develop MLN programs.
tuffy.infer	Provides MLN inference algorithms.
tuffy.learn	Provides weight learning in Tuffy.

Uses of MRF in tuffy.ground.partition

Fields in tuffy.ground.partition declared as MRF

MRF	Partition.mrf

Methods in tuffy.ground.partition that return MRF

MRF	PartitionScheme.getMRFByPartID(int pid)

Uses of MRF in tuffy.helper

Methods in tuffy.helper with parameters of type MRF

static void	Stats.dumpStats(MRF mrf)
static void	Stats.pullAtomReps(MRF mrf)
static java.lang.String	Stats.reportMostViolatedClauses(MRF mrf, int k)

Uses of MRF in tuffy.infer

Methods in tuffy.infer that return MRF

MRF	DataMover.loadMrfFromDb(MRF mrf, java.lang.String relAtoms, java.lang.String relClauses) Load the entire grounding result into memory as an MRF.
MRF	DataMover.loadMrfFromDb(java.lang.String relAtoms, java.lang.String relClauses)

Methods in tuffy.infer that return types with arguments of type MRF

private java.util.ArrayList<MRF>

MRF.split(int np) For research experiments! Split the MRF into multiple pieces by agglomerative clustering.

Methods in tuffy.infer with parameters of type MRF

MRF	DataMover.loadMrfFromDb(MRF mrf, java.lang.String relAtoms, java.lang.String relClauses) Load the entire grounding result into memory as an MRF.

Uses of MRF in tuffy.learn

Methods in tuffy.learn with parameters of type MRF

void	Learner.fillInCurrentWeight(MRF _mcsat) Initialize weight according to the log odd of training data.
void	DNLearner.getGradientAndD(MRF mcsat) Calculate the gradient and H^(-1)g by filling in DNLearner.currentD and DNLearner.currentGradient.
void	NaiveDNLearner.loadingTrainingData(MRF _mcsat) Deprecated. Loading training data's truth value into MRF.
abstract void	Learner.loadingTrainingData(MRF _mcsat) Reading from training data and fill it into atoms.
void	DNLearner.loadingTrainingData(MRF _mcsat) Load training data's truth value into MRF.
void	NaiveGDLearner.loadingTrainingData(MRF _mcsat) NEVER USE THIS IN REAL CIRCUMSTANCE...
boolean	NaiveDNLearner.updateWeight(MRF mcsat) Deprecated. Updating Learner.currentWeight using Diagonal Newton method.
abstract boolean	Learner.updateWeight(MRF mcsat) Update Learner.currentWeight to new weights according to information provided by mcsat instance, e.g., MCSAT#expectationOfViolation; This is a virtual function, each instance of Learner should materialize an adhoc version of this function.
boolean	DNLearner.updateWeight(MRF mcsat) Update Learner.currentWeight using Diagonal Newton method.
boolean	NaiveGDLearner.updateWeight(MRF mcsat) NEVER USE THIS IN REAL CIRCUMSTANCE...