public class GIS
extends java.lang.Object
| Modifier and Type | Field and Description |
|---|---|
static boolean |
PRINT_MESSAGES
Set this to false if you don't want messages about the progress of
model training displayed.
|
static double |
SMOOTHING_OBSERVATION
If we are using smoothing, this is used as the "number" of
times we want the trainer to imagine that it saw a feature that it
actually didn't see.
|
| Constructor and Description |
|---|
GIS() |
| Modifier and Type | Method and Description |
|---|---|
static GISModel |
trainModel(opennlp.model.EventStream eventStream)
Train a model using the GIS algorithm, assuming 100 iterations and no
cutoff.
|
static GISModel |
trainModel(opennlp.model.EventStream eventStream,
boolean smoothing)
Train a model using the GIS algorithm, assuming 100 iterations and no
cutoff.
|
static GISModel |
trainModel(opennlp.model.EventStream eventStream,
int iterations,
int cutoff)
Train a model using the GIS algorithm.
|
static GISModel |
trainModel(opennlp.model.EventStream eventStream,
int iterations,
int cutoff,
boolean smoothing,
boolean printMessagesWhileTraining)
Train a model using the GIS algorithm.
|
static GISModel |
trainModel(opennlp.model.EventStream eventStream,
int iterations,
int cutoff,
double sigma)
Train a model using the GIS algorithm.
|
static GISModel |
trainModel(int iterations,
opennlp.model.DataIndexer indexer)
Train a model using the GIS algorithm.
|
static GISModel |
trainModel(int iterations,
opennlp.model.DataIndexer indexer,
boolean smoothing)
Train a model using the GIS algorithm.
|
static GISModel |
trainModel(int iterations,
opennlp.model.DataIndexer indexer,
boolean printMessagesWhileTraining,
boolean smoothing,
opennlp.model.Prior modelPrior,
int cutoff)
Train a model using the GIS algorithm.
|
static GISModel |
trainModel(int iterations,
opennlp.model.DataIndexer indexer,
opennlp.model.Prior modelPrior,
int cutoff)
Train a model using the GIS algorithm with the specified number of iterations, data indexer, and prior.
|
public static boolean PRINT_MESSAGES
public static double SMOOTHING_OBSERVATION
public static GISModel trainModel(opennlp.model.EventStream eventStream) throws java.io.IOException
eventStream - The EventStream holding the data on which this model
will be trained.java.io.IOExceptionpublic static GISModel trainModel(opennlp.model.EventStream eventStream, boolean smoothing) throws java.io.IOException
eventStream - The EventStream holding the data on which this model
will be trained.smoothing - Defines whether the created trainer will use smoothing
while training the model.java.io.IOExceptionpublic static GISModel trainModel(opennlp.model.EventStream eventStream, int iterations, int cutoff) throws java.io.IOException
eventStream - The EventStream holding the data on which this model
will be trained.iterations - The number of GIS iterations to perform.cutoff - The number of times a feature must be seen in order
to be relevant for training.java.io.IOExceptionpublic static GISModel trainModel(opennlp.model.EventStream eventStream, int iterations, int cutoff, boolean smoothing, boolean printMessagesWhileTraining) throws java.io.IOException
eventStream - The EventStream holding the data on which this model
will be trained.iterations - The number of GIS iterations to perform.cutoff - The number of times a feature must be seen in order
to be relevant for training.smoothing - Defines whether the created trainer will use smoothing
while training the model.printMessagesWhileTraining - Determines whether training status messages are written to STDOUT.java.io.IOExceptionpublic static GISModel trainModel(opennlp.model.EventStream eventStream, int iterations, int cutoff, double sigma) throws java.io.IOException
eventStream - The EventStream holding the data on which this model
will be trained.iterations - The number of GIS iterations to perform.cutoff - The number of times a feature must be seen in order
to be relevant for training.sigma - The standard deviation for the gaussian smoother.java.io.IOExceptionpublic static GISModel trainModel(int iterations, opennlp.model.DataIndexer indexer, boolean smoothing)
iterations - The number of GIS iterations to perform.indexer - The object which will be used for event compilation.smoothing - Defines whether the created trainer will use smoothing while training the model.public static GISModel trainModel(int iterations, opennlp.model.DataIndexer indexer)
iterations - The number of GIS iterations to perform.indexer - The object which will be used for event compilation.public static GISModel trainModel(int iterations, opennlp.model.DataIndexer indexer, opennlp.model.Prior modelPrior, int cutoff)
iterations - The number of GIS iterations to perform.indexer - The object which will be used for event compilation.modelPrior - The prior distribution for the model.public static GISModel trainModel(int iterations, opennlp.model.DataIndexer indexer, boolean printMessagesWhileTraining, boolean smoothing, opennlp.model.Prior modelPrior, int cutoff)
iterations - The number of GIS iterations to perform.indexer - The object which will be used for event compilation.printMessagesWhileTraining - Determines whether training status messages are written to STDOUT.smoothing - Defines whether the created trainer will use smoothing while training the model.modelPrior - The prior distribution for the model.cutoff - The number of times a predicate must occur to be used in a model.Copyright ? 2008 Jason Baldridge, Gann Bierner, and Thomas Morton. All Rights Reserved.