edu.nyu.jet.chunk

Class GISTrainer

java.lang.Object

edu.nyu.jet.chunk.GISTrainer

Direct Known Subclasses:

LBFGSTrainer

public class GISTrainer
extends Object

An implementation of Generalized Iterative Scaling. The reference paper for this implementation was Adwait Ratnaparkhi's tech report at the University of Pennsylvania's Institute for Research in Cognitive Science, and is available at ftp://ftp.cis.upenn.edu/pub/ircs/tr/97-08.ps.Z. The slack parameter used in the above implementation has been removed by default from the computation and a method for updating with Gaussian smoothing has been added per Investigating GIS and Smoothing for Maximum Entropy Taggers, Clark and Curran (2002). http://acl.ldc.upenn.edu/E/E03/E03-1071.pdf The slack parameter can be used by setting useSlackParameter to true. Gaussian smoothing can be used by setting useGaussianSmoothing to true. A prior can be used to train models which converge to the distribution which minimizes the relative entropy between the distribution specified by the empirical constraints of the training data and the specified prior. By default, the uniform distribution is used as the prior.

Version:

$Revision: 1.7 $, $Date: 2010/09/06 08:02:18 $

Author:

Tom Morton, Jason Baldridge

Method Summary

Methods

Modifier and Type	Method and Description
void	setGaussianSigma(double sigmaValue) Sets whether this trainer will use smoothing while training the model.
void	setSmoothing(boolean smooth) Sets whether this trainer will use smoothing while training the model.
void	setSmoothingObservation(double timesSeen) Sets whether this trainer will use smoothing while training the model.
opennlp.maxent.GISModel	trainModel(opennlp.model.EventStream eventStream, int iterations, int cutoff) Trains a GIS model on the event in the specified event stream, using the specified number of iterations and the specified count cutoff.
opennlp.maxent.GISModel	trainModel(int iterations, opennlp.model.DataIndexer di, int cutoff) Train a model using the GIS algorithm.
opennlp.maxent.GISModel	trainModel(int iterations, opennlp.model.DataIndexer di, opennlp.model.Prior modelPrior, int cutoff) Train a model using the GIS algorithm.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Detail

setSmoothing

public void setSmoothing(boolean smooth)

Sets whether this trainer will use smoothing while training the model. This can improve model accuracy, though training will potentially take longer and use more memory. Model size will also be larger.

Parameters:

smooth - true if smoothing is desired, false if not

setSmoothingObservation

public void setSmoothingObservation(double timesSeen)

Sets whether this trainer will use smoothing while training the model. This can improve model accuracy, though training will potentially take longer and use more memory. Model size will also be larger.

Parameters:

timesSeen - the "number" of times we want the trainer to imagine it saw a feature that it actually didn't see

setGaussianSigma

public void setGaussianSigma(double sigmaValue)

Sets whether this trainer will use smoothing while training the model. This can improve model accuracy, though training will potentially take longer and use more memory. Model size will also be larger.

Parameters:

sigmaValue - set the sigmaValue for smoothing. useGaussianSmoothing is set to true automatically

trainModel

public opennlp.maxent.GISModel trainModel(opennlp.model.EventStream eventStream,
                                 int iterations,
                                 int cutoff)
                                   throws IOException

Trains a GIS model on the event in the specified event stream, using the specified number of iterations and the specified count cutoff.

Parameters:

eventStream - A stream of all events.

iterations - The number of iterations to use for GIS.

cutoff - The number of times a feature must occur to be included.

Returns:

A GIS model trained with specified

Throws:

IOException

trainModel

public opennlp.maxent.GISModel trainModel(int iterations,
                                 opennlp.model.DataIndexer di,
                                 int cutoff)

Train a model using the GIS algorithm.

Parameters:

iterations - The number of GIS iterations to perform.

di - The data indexer used to compress events in memory.

Returns:

The newly trained model, which can be used immediately or saved to disk using an opennlp.maxent.io.GISModelWriter object.

trainModel

public opennlp.maxent.GISModel trainModel(int iterations,
                                 opennlp.model.DataIndexer di,
                                 opennlp.model.Prior modelPrior,
                                 int cutoff)

Train a model using the GIS algorithm.

Parameters:

iterations - The number of GIS iterations to perform.

di - The data indexer used to compress events in memory.

modelPrior - The prior distribution used to train this model.

Returns:

The newly trained model, which can be used immediately or saved to disk using an opennlp.maxent.io.GISModelWriter object.