opennlp.tools.ml.maxent

## Class GISTrainer

- java.lang.Object
- - opennlp.tools.ml.AbstractTrainer
  - - opennlp.tools.ml.AbstractEventTrainer
    - - opennlp.tools.ml.maxent.GISTrainer

- All Implemented Interfaces:
    EventTrainer

      public class GISTrainer
      extends AbstractEventTrainer

  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.

- - ### Field Summary

    Fields
    Modifier and Type | Field and Description
    --- | ---
    `static double` | `LOG_LIKELIHOOD_THRESHOLD_DEFAULT`
    `static String` | `LOG_LIKELIHOOD_THRESHOLD_PARAM`
    `static String` | `MAXENT_VALUE`
    `static String` | `OLD_LL_THRESHOLD_PARAM` Deprecated.

    - ### Fields inherited from class opennlp.tools.ml.AbstractEventTrainer

      `DATA_INDEXER_ONE_PASS_REAL_VALUE, DATA_INDEXER_ONE_PASS_VALUE, DATA_INDEXER_PARAM, DATA_INDEXER_TWO_PASS_VALUE`

    - ### Fields inherited from class opennlp.tools.ml.AbstractTrainer

      `ALGORITHM_PARAM, CUTOFF_DEFAULT, CUTOFF_PARAM, ITERATIONS_DEFAULT, ITERATIONS_PARAM, TRAINER_TYPE_PARAM, VERBOSE_DEFAULT, VERBOSE_PARAM`

    - ### Fields inherited from interface opennlp.tools.ml.EventTrainer

      `EVENT_VALUE`

  - ### Constructor Summary

    Constructors
    Constructor and Description
    `GISTrainer()` Creates a new `GISTrainer` instance which does not print progress messages about training to STDOUT.

  - ### Method Summary

    All Methods Instance Methods Concrete Methods
    Modifier and Type | Method and Description
    --- | ---
    `MaxentModel` | `doTrain(DataIndexer indexer)`
    `void` | `init(TrainingParameters trainingParameters, Map<String,String> reportMap)`
    `boolean` | `isSortAndMerge()`
    `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.
    `GISModel` | `trainModel(int iterations, DataIndexer di)` Train a model using the GIS algorithm.
    `GISModel` | `trainModel(int iterations, DataIndexer di, int threads)` Train a model using the GIS algorithm.
    `GISModel` | `trainModel(int iterations, DataIndexer di, Prior modelPrior, int threads)` Train a model using the GIS algorithm.
    `GISModel` | `trainModel(ObjectStream<Event> eventStream)` Train a model using the GIS algorithm, assuming 100 iterations and no cutoff.
    `GISModel` | `trainModel(ObjectStream<Event> 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.

    - ### Methods inherited from class opennlp.tools.ml.AbstractEventTrainer

      `getDataIndexer, isValid, train, train, validate`

    - ### Methods inherited from class opennlp.tools.ml.AbstractTrainer

      `getAlgorithm, getCutoff, getIterations, init`

    - ### Methods inherited from class java.lang.Object

      `equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

    - ### Methods inherited from interface opennlp.tools.ml.EventTrainer

      `init`

- - ### Field Detail

    - #### OLD_LL_THRESHOLD_PARAM

          @Deprecated
          public static final String OLD_LL_THRESHOLD_PARAM

      Deprecated.
      See Also:
        Constant Field Values

    - #### LOG_LIKELIHOOD_THRESHOLD_PARAM

          public static final String LOG_LIKELIHOOD_THRESHOLD_PARAM

      See Also:
        Constant Field Values

    - #### LOG_LIKELIHOOD_THRESHOLD_DEFAULT

          public static final double LOG_LIKELIHOOD_THRESHOLD_DEFAULT

      See Also:
        Constant Field Values

    - #### MAXENT_VALUE

          public static final String MAXENT_VALUE

      See Also:
        Constant Field Values

  - ### Constructor Detail

    - #### GISTrainer

          public GISTrainer()

      Creates a new `GISTrainer` instance which does not print progress messages about training to STDOUT.

  - ### Method Detail

    - #### isSortAndMerge

          public boolean isSortAndMerge()

      Specified by:
        `isSortAndMerge` in class `AbstractEventTrainer`

    - #### init

          public void init(TrainingParameters trainingParameters,
                           Map<String,String> reportMap)

      Specified by:
        `init` in interface `EventTrainer`
      Overrides:
        `init` in class `AbstractTrainer`

    - #### doTrain

          public MaxentModel doTrain(DataIndexer indexer)
                              throws IOException

      Specified by:
        `doTrain` in class `AbstractEventTrainer`
      Throws:
        `IOException`

    - #### 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.

    - #### trainModel

          public GISModel trainModel(ObjectStream<Event> eventStream)
                              throws IOException

      Train a model using the GIS algorithm, assuming 100 iterations and no cutoff.
      Parameters:
        `eventStream` - The EventStream holding the data on which this model will be trained.
      Returns:
        The newly trained model, which can be used immediately or saved to disk using an opennlp.tools.ml.maxent.io.GISModelWriter object.
      Throws:
        `IOException`

    - #### trainModel

          public GISModel trainModel(ObjectStream<Event> 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 GISModel trainModel(int iterations,
                                     DataIndexer di)

      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.tools.ml.maxent.io.GISModelWriter object.

    - #### trainModel

          public GISModel trainModel(int iterations,
                                     DataIndexer di,
                                     int threads)

      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.
        `threads` -
      Returns:
        The newly trained model, which can be used immediately or saved to disk using an opennlp.tools.ml.maxent.io.GISModelWriter object.

    - #### trainModel

          public GISModel trainModel(int iterations,
                                     DataIndexer di,
                                     Prior modelPrior,
                                     int threads)

      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.tools.ml.maxent.io.GISModelWriter object.

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