Class QNTrainer

java.lang.Object
opennlp.tools.ml.AbstractTrainer<opennlp.tools.util.TrainingParameters>
opennlp.tools.ml.AbstractEventTrainer<opennlp.tools.util.TrainingParameters>
opennlp.tools.ml.maxent.quasinewton.QNTrainer
All Implemented Interfaces:
opennlp.tools.commons.Trainer<opennlp.tools.util.TrainingParameters>, opennlp.tools.ml.EventTrainer<opennlp.tools.util.TrainingParameters>
public class QNTrainer extends opennlp.tools.ml.AbstractEventTrainer<opennlp.tools.util.TrainingParameters>
A Maxent model trainer using the L-BFGS algorithm.
See Also:

  • Field Summary

    Fields
    Modifier and Type
    Field
    Description
    static final double
    L1COST_DEFAULT
    The default L1-cost value is 0.1d.
    static final String
    L1COST_PARAM
     
    static final double
    L2COST_DEFAULT
    The default L2-cost value is 0.1d.
    static final String
    L2COST_PARAM
     
    static final int
    M_DEFAULT
    The default number of Hessian updates to store is 15.
    static final String
    M_PARAM
     
    static final int
    MAX_FCT_EVAL_DEFAULT
    The default maximum number of function evaluations is 30,000.
    static final String
    MAX_FCT_EVAL_PARAM
     
    static final String
    MAXENT_QN_VALUE
     
    static final int
    THREADS_DEFAULT
     
    static final String
    THREADS_PARAM
     

    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 interface opennlp.tools.ml.EventTrainer

    EVENT_VALUE

  • Constructor Summary

    Constructors
    Constructor
    Description
    QNTrainer()
    Initializes a QNTrainer.
    QNTrainer(int m)
    Initializes a QNTrainer with the specified parameter m.
    QNTrainer(int m, int maxFctEval)
    Initializes a QNTrainer with the specified parameters.
    QNTrainer(opennlp.tools.util.TrainingParameters parameters)
    Initializes a QNTrainer with the specified parameters.

  • Method Summary

    Modifier and Type
    Method
    Description
    opennlp.tools.ml.model.AbstractModel
    doTrain(opennlp.tools.ml.model.DataIndexer<opennlp.tools.util.TrainingParameters> indexer)
     
    void
    init(opennlp.tools.util.TrainingParameters trainingParameters, Map<String,String> reportMap)
     
    boolean
    isSortAndMerge()
     
    QNModel
    trainModel(int iterations, opennlp.tools.ml.model.DataIndexer<opennlp.tools.util.TrainingParameters> indexer)
    Trains a model using the QN algorithm.
    void
    validate()
     

    Methods inherited from class opennlp.tools.ml.AbstractEventTrainer

    getDataIndexer, train, train

    Methods inherited from class opennlp.tools.ml.AbstractTrainer

    getAlgorithm, getCutoff, getIterations, getTrainingConfiguration, init

    Methods inherited from class Object

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

    Methods inherited from interface opennlp.tools.commons.Trainer

    init

  • Field Details

  • Constructor Details

    • QNTrainer

      public QNTrainer()
      Initializes a QNTrainer.

    • QNTrainer

      public QNTrainer(opennlp.tools.util.TrainingParameters parameters)
      Initializes a QNTrainer with the specified parameters.
      Parameters:
      parameters - The TrainingParameters to use.

    • QNTrainer

      public QNTrainer(int m)
      Initializes a QNTrainer with the specified parameter m.
      Parameters:
      m - The number of hessian updates to store.

    • QNTrainer

      public QNTrainer(int m, int maxFctEval)
      Initializes a QNTrainer with the specified parameters.
      Parameters:
      m - The number of hessian updates to store.

  • Method Details

    • init

      public void init(opennlp.tools.util.TrainingParameters trainingParameters, Map<String,String> reportMap)
      Specified by:
      init in interface opennlp.tools.commons.Trainer<opennlp.tools.util.TrainingParameters>
      Overrides:
      init in class opennlp.tools.ml.AbstractTrainer<opennlp.tools.util.TrainingParameters>

    • validate

      public void validate()
      Overrides:
      validate in class opennlp.tools.ml.AbstractEventTrainer<opennlp.tools.util.TrainingParameters>

    • isSortAndMerge

      public boolean isSortAndMerge()
      Specified by:
      isSortAndMerge in class opennlp.tools.ml.AbstractEventTrainer<opennlp.tools.util.TrainingParameters>

    • doTrain

      public opennlp.tools.ml.model.AbstractModel doTrain(opennlp.tools.ml.model.DataIndexer<opennlp.tools.util.TrainingParameters> indexer) throws IOException
      Specified by:
      doTrain in class opennlp.tools.ml.AbstractEventTrainer<opennlp.tools.util.TrainingParameters>
      Throws:
      IOException

    • trainModel

      public QNModel trainModel(int iterations, opennlp.tools.ml.model.DataIndexer<opennlp.tools.util.TrainingParameters> indexer)
      Trains a model using the QN algorithm.
      Parameters:
      iterations - The number of QN iterations to perform.
      indexer - The DataIndexer used to compress events in memory.
      Returns:
      A trained QNModel which can be used immediately or saved to disk using an QNModelWriter.
      Throws:
      IllegalArgumentException - Thrown if parameters were invalid.