/// <summary>
/// Train a model using the GIS algorithm.
/// </summary>
/// <param name="iterations">
/// The number of GIS iterations to perform. </param>
/// <param name="indexer">
/// The object which will be used for event compilation. </param>
/// <param name="printMessagesWhileTraining">
/// Determines whether training status messages are written to STDOUT. </param>
/// <param name="smoothing">
/// Defines whether the created trainer will use smoothing while
/// training the model. </param>
/// <param name="modelPrior">
/// The prior distribution for the model. </param>
/// <param name="cutoff">
/// The number of times a predicate must occur to be used in a model. </param>
/// <returns> The newly trained model, which can be used immediately or saved to
/// disk using an opennlp.maxent.io.GISModelWriter object. </returns>
public static GISModel trainModel(int iterations, DataIndexer indexer, bool printMessagesWhileTraining,
bool smoothing, Prior modelPrior, int cutoff, int threads)
{
GISTrainer trainer = new GISTrainer(printMessagesWhileTraining);
trainer.Smoothing = smoothing;
trainer.SmoothingObservation = SMOOTHING_OBSERVATION;
if (modelPrior == null)
{
modelPrior = new UniformPrior();
}
return(trainer.trainModel(iterations, indexer, modelPrior, cutoff, threads));
}
/// <summary>
/// Train a model using the GIS algorithm.
/// </summary>
/// <param name="iterations">
/// The number of GIS iterations to perform. </param>
/// <param name="indexer">
/// The object which will be used for event compilation. </param>
/// <param name="printMessagesWhileTraining">
/// Determines whether training status messages are written to STDOUT. </param>
/// <param name="smoothing">
/// Defines whether the created trainer will use smoothing while
/// training the model. </param>
/// <param name="modelPrior">
/// The prior distribution for the model. </param>
/// <param name="cutoff">
/// The number of times a predicate must occur to be used in a model. </param>
/// <returns> The newly trained model, which can be used immediately or saved to
/// disk using an opennlp.maxent.io.GISModelWriter object. </returns>
public static GISModel trainModel(int iterations, DataIndexer indexer, bool printMessagesWhileTraining,
bool smoothing, Prior modelPrior, int cutoff)
{
return(trainModel(iterations, indexer, printMessagesWhileTraining, smoothing, modelPrior, cutoff, 1));
}
/// <summary>
/// Train a model using the GIS algorithm.
/// </summary>
/// <param name="iterations">
/// The number of GIS iterations to perform. </param>
/// <param name="indexer">
/// The object which will be used for event compilation. </param>
/// <returns> The newly trained model, which can be used immediately or saved to
/// disk using an opennlp.maxent.io.GISModelWriter object. </returns>
public static GISModel trainModel(int iterations, DataIndexer indexer)
{
return(trainModel(iterations, indexer, true, false, null, 0));
}
/// <summary>
/// Train a model using the GIS algorithm with the specified number of
/// iterations, data indexer, and prior.
/// </summary>
/// <param name="iterations">
/// The number of GIS iterations to perform. </param>
/// <param name="indexer">
/// The object which will be used for event compilation. </param>
/// <param name="modelPrior">
/// The prior distribution for the model. </param>
/// <returns> The newly trained model, which can be used immediately or saved to
/// disk using an opennlp.maxent.io.GISModelWriter object. </returns>
public static GISModel trainModel(int iterations, DataIndexer indexer, Prior modelPrior, int cutoff)
{
return(trainModel(iterations, indexer, true, false, modelPrior, cutoff));
}
/// <summary>
/// Train a model using the GIS algorithm.
/// </summary>
/// <param name="iterations">
/// The number of GIS iterations to perform. </param>
/// <param name="indexer">
/// The object which will be used for event compilation. </param>
/// <param name="smoothing">
/// Defines whether the created trainer will use smoothing while
/// training the model. </param>
/// <returns> The newly trained model, which can be used immediately or saved to
/// disk using an opennlp.maxent.io.GISModelWriter object. </returns>
public static GISModel trainModel(int iterations, DataIndexer indexer, bool smoothing)
{
return(trainModel(iterations, indexer, true, smoothing, null, 0));
}
