Package opennlp.tools.ml.naivebayes

# Class NaiveBayesTrainer

java.lang.Object
opennlp.tools.ml.AbstractTrainer<opennlp.tools.util.TrainingParameters>
opennlp.tools.ml.AbstractEventTrainer<opennlp.tools.util.TrainingParameters>
opennlp.tools.ml.naivebayes.NaiveBayesTrainer

All Implemented Interfaces:
  `opennlp.tools.commons.Trainer<opennlp.tools.util.TrainingParameters>`, `opennlp.tools.ml.EventTrainer<opennlp.tools.util.TrainingParameters>`

public class NaiveBayesTrainer extends opennlp.tools.ml.AbstractEventTrainer<opennlp.tools.util.TrainingParameters>
Trains `models` using the combination of EM algorithm and Naive Bayes classifier which is described in:

Text Classification from Labeled and Unlabeled Documents using EM Nigam, McCallum, et al. paper of 2000

See Also:
  - `NaiveBayesModel`
  - `AbstractEventTrainer`

- ## Field Summary

  Fields
  Modifier and Type
  Field
  Description
  `static final String`
  `NAIVE_BAYES_VALUE`

  ### 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
  `NaiveBayesTrainer()`
  Instantiates a `NaiveBayesTrainer` with default training parameters.
  `NaiveBayesTrainer(opennlp.tools.util.TrainingParameters parameters)`
  Instantiates a `NaiveBayesTrainer` with specific `TrainingParameters`.

- ## Method Summary

  Modifier and Type
  Method
  Description
  `opennlp.tools.ml.model.AbstractModel`
  `doTrain(opennlp.tools.ml.model.DataIndexer<opennlp.tools.util.TrainingParameters> indexer)`
  `boolean`
  `isSortAndMerge()`
  `opennlp.tools.ml.model.AbstractModel`
  `trainModel(opennlp.tools.ml.model.DataIndexer<opennlp.tools.util.TrainingParameters> di)`
  Trains a `NaiveBayesModel` with given parameters.

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

  `getDataIndexer, train, train, validate`

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

  `getAlgorithm, getCutoff, getIterations, getTrainingConfiguration, init, init`

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

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

  ### Methods inherited from interface opennlp.tools.commons.Trainer

  `init, init`

- ## Field Details

  - ### NAIVE_BAYES_VALUE

    public static final String NAIVE_BAYES_VALUE
    See Also:
      - Constant Field Values

- ## Constructor Details

  - ### NaiveBayesTrainer

    public NaiveBayesTrainer()
    Instantiates a `NaiveBayesTrainer` with default training parameters.

  - ### NaiveBayesTrainer

    public NaiveBayesTrainer(opennlp.tools.util.TrainingParameters parameters)
    Instantiates a `NaiveBayesTrainer` with specific `TrainingParameters`.
    Parameters:
      `parameters` - The `parameter` to use.

- ## Method Details

  - ### 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 opennlp.tools.ml.model.AbstractModel trainModel(opennlp.tools.ml.model.DataIndexer<opennlp.tools.util.TrainingParameters> di)
    Trains a `NaiveBayesModel` with given parameters.
    Parameters:
      `di` - The `DataIndexer` used as data input.
    Returns:
      A valid, trained `Naive Bayes model`.