Package | Description |
---|---|
opennlp.tools.ml | |
opennlp.tools.ml.maxent |
Provides main functionality of the maxent package including data structures and
algorithms for parameter estimation.
|
opennlp.tools.ml.maxent.quasinewton | |
opennlp.tools.ml.model | |
opennlp.tools.ml.perceptron |
Modifier and Type | Method and Description |
---|---|
DataIndexer |
AbstractEventTrainer.getDataIndexer(ObjectStream<Event> events) |
Modifier and Type | Method and Description |
---|---|
abstract MaxentModel |
AbstractEventTrainer.doTrain(DataIndexer indexer) |
Modifier and Type | Method and Description |
---|---|
AbstractModel |
GIS.doTrain(DataIndexer indexer) |
static GISModel |
GIS.trainModel(int iterations,
DataIndexer indexer)
Train a model using the GIS algorithm.
|
static GISModel |
GIS.trainModel(int iterations,
DataIndexer indexer,
boolean smoothing)
Train a model using the GIS algorithm.
|
static GISModel |
GIS.trainModel(int iterations,
DataIndexer indexer,
boolean printMessagesWhileTraining,
boolean smoothing,
Prior modelPrior,
int cutoff)
Train a model using the GIS algorithm.
|
static GISModel |
GIS.trainModel(int iterations,
DataIndexer indexer,
boolean printMessagesWhileTraining,
boolean smoothing,
Prior modelPrior,
int cutoff,
int threads)
Train a model using the GIS algorithm.
|
static GISModel |
GIS.trainModel(int iterations,
DataIndexer indexer,
Prior modelPrior,
int cutoff)
Train a model using the GIS algorithm with the specified number of
iterations, data indexer, and prior.
|
Modifier and Type | Method and Description |
---|---|
AbstractModel |
QNTrainer.doTrain(DataIndexer indexer) |
QNModel |
QNTrainer.trainModel(int iterations,
DataIndexer indexer) |
Constructor and Description |
---|
NegLogLikelihood(DataIndexer indexer) |
ParallelNegLogLikelihood(DataIndexer indexer,
int threads) |
Modifier and Type | Class and Description |
---|---|
class |
AbstractDataIndexer
Abstract class for collecting event and context counts used in training.
|
class |
OnePassDataIndexer
An indexer for maxent model data which handles cutoffs for uncommon
contextual predicates and provides a unique integer index for each of the
predicates.
|
class |
OnePassRealValueDataIndexer
An indexer for maxent model data which handles cutoffs for uncommon
contextual predicates and provides a unique integer index for each of the
predicates and maintains event values.
|
class |
TwoPassDataIndexer
Collecting event and context counts by making two passes over the events.
|
Modifier and Type | Method and Description |
---|---|
AbstractModel |
PerceptronTrainer.doTrain(DataIndexer indexer) |
AbstractModel |
PerceptronTrainer.trainModel(int iterations,
DataIndexer di,
int cutoff) |
AbstractModel |
PerceptronTrainer.trainModel(int iterations,
DataIndexer di,
int cutoff,
boolean useAverage) |
Copyright © 2015 The Apache Software Foundation. All rights reserved.