Uses of Interface opennlp.tools.ml.model.DataIndexer (Apache OpenNLP Tools 1.9.5 API)
Date: 2026-06-18

## Uses of Interface
opennlp.tools.ml.model.DataIndexer

- Packages that use DataIndexer
  Package | Description
  --- | ---
  opennlp.tools.ml |
  opennlp.tools.ml.maxent | Provides main functionality of the maxent package including data structures and algorithms for parameter estimation.
  opennlp.tools.ml.maxent.quasinewton |
  opennlp.tools.ml.model |
  opennlp.tools.ml.naivebayes |
  opennlp.tools.ml.perceptron |

- - ### Uses of DataIndexer in opennlp.tools.ml

    Methods in opennlp.tools.ml that return DataIndexer
    Modifier and Type | Method and Description
    --- | ---
    `DataIndexer` | AbstractEventTrainer.`getDataIndexer(ObjectStream<Event> events)`

    Methods in opennlp.tools.ml with parameters of type DataIndexer
    Modifier and Type | Method and Description
    --- | ---
    `abstract MaxentModel` | AbstractEventTrainer.`doTrain(DataIndexer indexer)`
    `MaxentModel` | AbstractEventTrainer.`train(DataIndexer indexer)`
    `MaxentModel` | EventTrainer.`train(DataIndexer indexer)`

  - ### Uses of DataIndexer in opennlp.tools.ml.maxent

    Methods in opennlp.tools.ml.maxent with parameters of type DataIndexer
    Modifier and Type | Method and Description
    --- | ---
    `MaxentModel` | GISTrainer.`doTrain(DataIndexer indexer)`
    `GISModel` | GISTrainer.`trainModel(int iterations, DataIndexer di)` Train a model using the GIS algorithm.
    `GISModel` | GISTrainer.`trainModel(int iterations, DataIndexer di, int threads)` Train a model using the GIS algorithm.
    `GISModel` | GISTrainer.`trainModel(int iterations, DataIndexer di, Prior modelPrior, int threads)` Train a model using the GIS algorithm.

  - ### Uses of DataIndexer in opennlp.tools.ml.maxent.quasinewton

    Methods in opennlp.tools.ml.maxent.quasinewton with parameters of type DataIndexer
    Modifier and Type | Method and Description
    --- | ---
    `AbstractModel` | QNTrainer.`doTrain(DataIndexer indexer)`
    `QNModel` | QNTrainer.`trainModel(int iterations, DataIndexer indexer)`

    Constructors in opennlp.tools.ml.maxent.quasinewton with parameters of type DataIndexer
    Constructor and Description
    `NegLogLikelihood(DataIndexer indexer)`
    `ParallelNegLogLikelihood(DataIndexer indexer, int threads)`

  - ### Uses of DataIndexer in opennlp.tools.ml.model

    Classes in opennlp.tools.ml.model that implement DataIndexer
    Modifier and Type | Class and Description
    --- | ---
    `class` | `AbstractDataIndexer` Abstract class for collecting event and context counts used in training.
    `class` | `OnePassDataIndexer` An indexer for maxent model data which handles cutoffs for uncommon contextual predicates and provides a unique integer index for each of the predicates.
    `class` | `OnePassRealValueDataIndexer` An indexer for maxent model data which handles cutoffs for uncommon contextual predicates and provides a unique integer index for each of the predicates and maintains event values.
    `class` | `TwoPassDataIndexer` Collecting event and context counts by making two passes over the events.

    Methods in opennlp.tools.ml.model that return DataIndexer
    Modifier and Type | Method and Description
    --- | ---
    `static DataIndexer` | DataIndexerFactory.`getDataIndexer(TrainingParameters parameters, Map<String,String> reportMap)`

  - ### Uses of DataIndexer in opennlp.tools.ml.naivebayes

    Methods in opennlp.tools.ml.naivebayes with parameters of type DataIndexer
    Modifier and Type | Method and Description
    --- | ---
    `AbstractModel` | NaiveBayesTrainer.`doTrain(DataIndexer indexer)`
    `AbstractModel` | NaiveBayesTrainer.`trainModel(DataIndexer di)`

  - ### Uses of DataIndexer in opennlp.tools.ml.perceptron

    Methods in opennlp.tools.ml.perceptron with parameters of type DataIndexer
    Modifier and Type | Method and Description
    --- | ---
    `AbstractModel` | PerceptronTrainer.`doTrain(DataIndexer indexer)`
    `AbstractModel` | PerceptronTrainer.`trainModel(int iterations, DataIndexer di, int cutoff)`
    `AbstractModel` | PerceptronTrainer.`trainModel(int iterations, DataIndexer di, int cutoff, boolean useAverage)`

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