Modifier and Type | Field and Description |
---|---|
protected Database |
InferenceApplication.database |
Modifier and Type | Method and Description |
---|---|
protected PersistedAtomManager |
InferenceApplication.createAtomManager(Database database) |
static InferenceApplication |
InferenceApplication.getInferenceApplication(String className,
List<Rule> rules,
Database database)
Construct an inference application given the data.
|
double |
InferenceApplication.inference(boolean commitAtoms,
boolean reset,
List<Evaluator> evaluators,
Database truthDatabase)
Minimize the total weighted incompatibility of the atoms according to the rules,
and optionally commit the updated atoms back to the database.
|
Constructor and Description |
---|
InferenceApplication(List<Rule> rules,
Database database) |
InferenceApplication(List<Rule> rules,
Database database,
boolean relaxHardConstraints) |
Modifier and Type | Method and Description |
---|---|
protected PersistedAtomManager |
LazyMPEInference.createAtomManager(Database db) |
Constructor and Description |
---|
ADMMInference(List<Rule> rules,
Database db) |
DCDInference(List<Rule> rules,
Database db) |
DCDStreamingInference(List<Rule> rules,
Database database) |
LazyMPEInference(List<Rule> rules,
Database db) |
MPEInference(List<Rule> rules,
Database db) |
MPEInference(List<Rule> rules,
Database db,
boolean relaxHardConstraints) |
SGDInference(List<Rule> rules,
Database db) |
SGDStreamingInference(List<Rule> rules,
Database database) |
Modifier and Type | Method and Description |
---|---|
protected PersistedAtomManager |
OnlineInference.createAtomManager(Database database) |
Constructor and Description |
---|
OnlineInference(List<Rule> rules,
Database database) |
OnlineInference(List<Rule> rules,
Database database,
boolean relaxHardConstraints) |
SGDOnlineInference(List<Rule> rules,
Database database) |
Modifier and Type | Field and Description |
---|---|
protected Database |
WeightLearningApplication.observedDB |
protected Database |
WeightLearningApplication.rvDB |
Modifier and Type | Method and Description |
---|---|
static WeightLearningApplication |
WeightLearningApplication.getWLA(String name,
List<Rule> rules,
Database randomVariableDatabase,
Database observedTruthDatabase)
Construct a weight learning application given the data.
|
Constructor and Description |
---|
TrainingMap(PersistedAtomManager targets,
Database truthDatabase)
Initializes the training map of RandomVariableAtoms ObservedAtoms.
|
VotedPerceptron(List<Rule> rules,
Database rvDB,
Database observedDB) |
WeightLearningApplication(List<Rule> rules,
Database rvDB,
Database observedDB) |
Constructor and Description |
---|
MaxLikelihoodMPE(List<Rule> rules,
Database rvDB,
Database observedDB) |
MaxLikelihoodMPE(Model model,
Database rvDB,
Database observedDB) |
MaxPiecewisePseudoLikelihood(List<Rule> rules,
Database rvDB,
Database observedDB) |
MaxPiecewisePseudoLikelihood(Model model,
Database rvDB,
Database observedDB) |
Constructor and Description |
---|
Hyperband(List<Rule> rules,
Database rvDB,
Database observedDB) |
Hyperband(Model model,
Database rvDB,
Database observedDB) |
InitialWeightHyperband(List<Rule> rules,
Database rvDB,
Database observedDB) |
InitialWeightHyperband(Model model,
Database rvDB,
Database observedDB) |
Constructor and Description |
---|
GaussianProcessPrior(List<Rule> rules,
Database rvDB,
Database observedDB) |
GaussianProcessPrior(Model model,
Database rvDB,
Database observedDB) |
Modifier and Type | Method and Description |
---|---|
Database |
DataStore.getDatabase(Partition write,
Partition... read)
Creates a Database that can read from and write to a
Partition and
optionally read from additional Partitions. |
Database |
DataStore.getDatabase(Partition write,
Set<StandardPredicate> toClose,
Partition... read)
Creates a Database that can read from and write to a
Partition and
optionally read from additional Partitions. |
Database |
DataStore.getDatabase(Partition write,
StandardPredicate[] toClose,
Partition... read) |
Modifier and Type | Method and Description |
---|---|
Iterable<Database> |
DataStore.getOpenDatabases()
Get all the currenly open databases associated with this data store.
|
Modifier and Type | Field and Description |
---|---|
protected Database |
AtomManager.db |
protected Database |
AtomCache.db |
Modifier and Type | Method and Description |
---|---|
Database |
AtomManager.getDatabase() |
Constructor and Description |
---|
AtomCache(Database db)
Constructs a new AtomCache for a Database.
|
AtomManager(Database db) |
LazyAtomManager(Database db) |
OnlineAtomManager(Database database,
InitialValue initialValue) |
PersistedAtomManager(Database db) |
PersistedAtomManager(Database db,
boolean prebuiltCache) |
PersistedAtomManager(Database db,
boolean prebuiltCache,
InitialValue initialValueOnIllegalAccess)
Constructs a PersistedAtomManager with a built-in set of all the database's persisted RandomVariableAtoms.
|
SimpleAtomManager(Database db) |
Modifier and Type | Class and Description |
---|---|
class |
RDBMSDatabase
A view on the datastore with specific partitions activated.
|
Modifier and Type | Method and Description |
---|---|
Database |
RDBMSDataStore.getDatabase(Partition write,
Partition... read) |
Database |
RDBMSDataStore.getDatabase(Partition write,
Set<StandardPredicate> toClose,
Partition... read) |
Database |
RDBMSDataStore.getDatabase(Partition write,
StandardPredicate[] toClose,
Partition... read) |
Modifier and Type | Method and Description |
---|---|
Iterable<Database> |
RDBMSDataStore.getOpenDatabases() |
Modifier and Type | Method and Description |
---|---|
void |
Evaluator.compute(Database rvDB,
Database truthDB,
StandardPredicate predicate) |
void |
Evaluator.compute(Database rvDB,
Database truthDB,
StandardPredicate predicate,
boolean rvDBCached)
A convenience call for those who don't want to create a training map directly.
|
Modifier and Type | Method and Description |
---|---|
static QueryResultIterable |
PartialGrounding.getPartialGroundingResults(Rule rule,
Set<StandardPredicate> partialPredicates,
Database db) |
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