## Uses of Class
opennlp.tools.util.TrainingParameters

- Packages that use TrainingParameters
  Package | Description
  --- | ---
  opennlp.tools.chunker | Package related to finding non-recursive syntactic annotation such as noun phrase chunks.
  opennlp.tools.doccat | Package for classifying a document into a category.
  opennlp.tools.langdetect |
  opennlp.tools.lemmatizer | Package related with the lemmatizer tool
  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 |
  opennlp.tools.namefind | Package related to finding proper names and numeric amounts.
  opennlp.tools.parser | Package containing common code for performing full syntactic parsing.
  opennlp.tools.parser.chunking | Package containing code for performing full syntactic parsing using shift/reduce-style decisions.
  opennlp.tools.parser.treeinsert | Package containing experimental code for performing full syntactic parsing using attachment decisions.
  opennlp.tools.postag | Package related to part-of-speech tagging.
  opennlp.tools.sentdetect | Package related to identifying sentece boundries.
  opennlp.tools.tokenize | Contains classes related to finding token or words in a string.
  opennlp.tools.util | Package containing utility data structures and algorithms used by multiple other packages.
  opennlp.tools.util.model |

- - ### Uses of TrainingParameters in opennlp.tools.chunker

    Methods in opennlp.tools.chunker with parameters of type TrainingParameters
    Modifier and Type | Method and Description
    --- | ---
    `static ChunkerModel` | ChunkerME.`train(String lang, ObjectStream<ChunkSample> in, TrainingParameters mlParams, ChunkerFactory factory)`

    Constructors in opennlp.tools.chunker with parameters of type TrainingParameters
    Constructor and Description
    `ChunkerCrossValidator(String languageCode, TrainingParameters params, ChunkerFactory factory, ChunkerEvaluationMonitor... listeners)`

  - ### Uses of TrainingParameters in opennlp.tools.doccat

    Methods in opennlp.tools.doccat with parameters of type TrainingParameters
    Modifier and Type | Method and Description
    --- | ---
    `static DoccatModel` | DocumentCategorizerME.`train(String languageCode, ObjectStream<DocumentSample> samples, TrainingParameters mlParams, DoccatFactory factory)`

    Constructors in opennlp.tools.doccat with parameters of type TrainingParameters
    Constructor and Description
    `DoccatCrossValidator(String languageCode, TrainingParameters mlParams, DoccatFactory factory, DoccatEvaluationMonitor... listeners)` Creates a `DoccatCrossValidator` with the given `FeatureGenerator`s.

  - ### Uses of TrainingParameters in opennlp.tools.langdetect

    Methods in opennlp.tools.langdetect with parameters of type TrainingParameters
    Modifier and Type | Method and Description
    --- | ---
    `static LanguageDetectorModel` | LanguageDetectorME.`train(ObjectStream<LanguageSample> samples, TrainingParameters mlParams, LanguageDetectorFactory factory)`

    Constructors in opennlp.tools.langdetect with parameters of type TrainingParameters
    Constructor and Description
    `LanguageDetectorCrossValidator(TrainingParameters mlParams, LanguageDetectorFactory factory, LanguageDetectorEvaluationMonitor... listeners)` Creates a `LanguageDetectorCrossValidator` with the given `FeatureGenerator`s.

  - ### Uses of TrainingParameters in opennlp.tools.lemmatizer

    Methods in opennlp.tools.lemmatizer with parameters of type TrainingParameters
    Modifier and Type | Method and Description
    --- | ---
    `static LemmatizerModel` | LemmatizerME.`train(String languageCode, ObjectStream<LemmaSample> samples, TrainingParameters trainParams, LemmatizerFactory posFactory)`

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

    Fields in opennlp.tools.ml declared as TrainingParameters
    Modifier and Type | Field and Description
    --- | ---
    `protected TrainingParameters` | AbstractTrainer.`trainingParameters`

    Methods in opennlp.tools.ml with parameters of type TrainingParameters
    Modifier and Type | Method and Description
    --- | ---
    `static EventModelSequenceTrainer` | TrainerFactory.`getEventModelSequenceTrainer(TrainingParameters trainParams, Map<String,String> reportMap)`
    `static EventTrainer` | TrainerFactory.`getEventTrainer(TrainingParameters trainParams, Map<String,String> reportMap)`
    `static SequenceTrainer` | TrainerFactory.`getSequenceModelTrainer(TrainingParameters trainParams, Map<String,String> reportMap)`
    `static TrainerFactory.TrainerType` | TrainerFactory.`getTrainerType(TrainingParameters trainParams)` Determines the trainer type based on the ALGORITHM_PARAM value.
    `void` | EventModelSequenceTrainer.`init(TrainingParameters trainParams, Map<String,String> reportMap)`
    `void` | SequenceTrainer.`init(TrainingParameters trainParams, Map<String,String> reportMap)`
    `void` | AbstractTrainer.`init(TrainingParameters trainingParameters, Map<String,String> reportMap)`
    `void` | EventTrainer.`init(TrainingParameters trainingParams, Map<String,String> reportMap)`
    `static boolean` | TrainerFactory.`isValid(TrainingParameters trainParams)`

    Constructors in opennlp.tools.ml with parameters of type TrainingParameters
    Constructor and Description
    `AbstractEventTrainer(TrainingParameters parameters)`
    `AbstractTrainer(TrainingParameters parameters)`

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

    Methods in opennlp.tools.ml.maxent with parameters of type TrainingParameters
    Modifier and Type | Method and Description
    --- | ---
    `void` | GISTrainer.`init(TrainingParameters trainingParameters, Map<String,String> reportMap)`

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

    Methods in opennlp.tools.ml.maxent.quasinewton with parameters of type TrainingParameters
    Modifier and Type | Method and Description
    --- | ---
    `void` | QNTrainer.`init(TrainingParameters trainingParameters, Map<String,String> reportMap)`

    Constructors in opennlp.tools.ml.maxent.quasinewton with parameters of type TrainingParameters
    Constructor and Description
    `QNTrainer(TrainingParameters parameters)`

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

    Fields in opennlp.tools.ml.model declared as TrainingParameters
    Modifier and Type | Field and Description
    --- | ---
    `protected TrainingParameters` | AbstractDataIndexer.`trainingParameters`

    Methods in opennlp.tools.ml.model with parameters of type TrainingParameters
    Modifier and Type | Method and Description
    --- | ---
    `static DataIndexer` | DataIndexerFactory.`getDataIndexer(TrainingParameters parameters, Map<String,String> reportMap)`
    `void` | DataIndexer.`init(TrainingParameters trainParams, Map<String,String> reportMap)` Sets parameters used during the data indexing.
    `void` | AbstractDataIndexer.`init(TrainingParameters indexingParameters, Map<String,String> reportMap)`

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

    Constructors in opennlp.tools.ml.naivebayes with parameters of type TrainingParameters
    Constructor and Description
    `NaiveBayesTrainer(TrainingParameters parameters)`

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

    Constructors in opennlp.tools.ml.perceptron with parameters of type TrainingParameters
    Constructor and Description
    `PerceptronTrainer(TrainingParameters parameters)`

  - ### Uses of TrainingParameters in opennlp.tools.namefind

    Methods in opennlp.tools.namefind with parameters of type TrainingParameters
    Modifier and Type | Method and Description
    --- | ---
    `static TokenNameFinderModel` | NameFinderME.`train(String languageCode, String type, ObjectStream<NameSample> samples, TrainingParameters trainParams, TokenNameFinderFactory factory)`

    Constructors in opennlp.tools.namefind with parameters of type TrainingParameters
    Constructor and Description
    `TokenNameFinderCrossValidator(String languageCode, String type, TrainingParameters trainParams, byte[] featureGeneratorBytes, Map<String,Object> resources, SequenceCodec<String> codec, TokenNameFinderEvaluationMonitor... listeners)` Name finder cross validator
    `TokenNameFinderCrossValidator(String languageCode, String type, TrainingParameters trainParams, byte[] featureGeneratorBytes, Map<String,Object> resources, TokenNameFinderEvaluationMonitor... listeners)`
    `TokenNameFinderCrossValidator(String languageCode, String type, TrainingParameters trainParams, TokenNameFinderFactory factory, TokenNameFinderEvaluationMonitor... listeners)`

  - ### Uses of TrainingParameters in opennlp.tools.parser

    Methods in opennlp.tools.parser with parameters of type TrainingParameters
    Modifier and Type | Method and Description
    --- | ---
    `static Dictionary` | AbstractBottomUpParser.`buildDictionary(ObjectStream<Parse> data, HeadRules rules, TrainingParameters params)` Creates a n-gram dictionary from the specified data stream using the specified head rule and specified cut-off.

    Constructors in opennlp.tools.parser with parameters of type TrainingParameters
    Constructor and Description
    `ParserCrossValidator(String languageCode, TrainingParameters params, HeadRules rules, ParserType parserType, ParserEvaluationMonitor... monitors)`

  - ### Uses of TrainingParameters in opennlp.tools.parser.chunking

    Methods in opennlp.tools.parser.chunking with parameters of type TrainingParameters
    Modifier and Type | Method and Description
    --- | ---
    `static ParserModel` | Parser.`train(String languageCode, ObjectStream<Parse> parseSamples, HeadRules rules, TrainingParameters mlParams)`

  - ### Uses of TrainingParameters in opennlp.tools.parser.treeinsert

    Methods in opennlp.tools.parser.treeinsert with parameters of type TrainingParameters
    Modifier and Type | Method and Description
    --- | ---
    `static ParserModel` | Parser.`train(String languageCode, ObjectStream<Parse> parseSamples, HeadRules rules, TrainingParameters mlParams)`

  - ### Uses of TrainingParameters in opennlp.tools.postag

    Methods in opennlp.tools.postag with parameters of type TrainingParameters
    Modifier and Type | Method and Description
    --- | ---
    `static POSModel` | POSTaggerME.`train(String languageCode, ObjectStream<POSSample> samples, TrainingParameters trainParams, POSTaggerFactory posFactory)`

    Constructors in opennlp.tools.postag with parameters of type TrainingParameters
    Constructor and Description
    `POSTaggerCrossValidator(String languageCode, TrainingParameters trainParam, File tagDictionary, byte[] featureGeneratorBytes, Map<String,Object> resources, Integer tagdicCutoff, String factoryClass, POSTaggerEvaluationMonitor... listeners)` Creates a `POSTaggerCrossValidator` that builds a ngram dictionary dynamically.
    `POSTaggerCrossValidator(String languageCode, TrainingParameters trainParam, POSTaggerFactory factory, POSTaggerEvaluationMonitor... listeners)` Creates a `POSTaggerCrossValidator` using the given `POSTaggerFactory`.

  - ### Uses of TrainingParameters in opennlp.tools.sentdetect

    Methods in opennlp.tools.sentdetect with parameters of type TrainingParameters
    Modifier and Type | Method and Description
    --- | ---
    `static SentenceModel` | SentenceDetectorME.`train(String languageCode, ObjectStream<SentenceSample> samples, boolean useTokenEnd, Dictionary abbreviations, TrainingParameters mlParams)` Deprecated. Use `SentenceDetectorME.train(String, ObjectStream, SentenceDetectorFactory, TrainingParameters)` and pass in af `SentenceDetectorFactory`.
    `static SentenceModel` | SentenceDetectorME.`train(String languageCode, ObjectStream<SentenceSample> samples, SentenceDetectorFactory sdFactory, TrainingParameters mlParams)`

    Constructors in opennlp.tools.sentdetect with parameters of type TrainingParameters
    Constructor and Description
    `SDCrossValidator(String languageCode, TrainingParameters params)` Deprecated. Use `SDCrossValidator(String, TrainingParameters, SentenceDetectorFactory, SentenceDetectorEvaluationMonitor...)` and pass in a `SentenceDetectorFactory`.
    `SDCrossValidator(String languageCode, TrainingParameters params, SentenceDetectorEvaluationMonitor... listeners)` Deprecated. use `SDCrossValidator(String, TrainingParameters, SentenceDetectorFactory, SentenceDetectorEvaluationMonitor...)` instead and pass in a TrainingParameters object.
    `SDCrossValidator(String languageCode, TrainingParameters params, SentenceDetectorFactory sdFactory, SentenceDetectorEvaluationMonitor... listeners)`

  - ### Uses of TrainingParameters in opennlp.tools.tokenize

    Methods in opennlp.tools.tokenize with parameters of type TrainingParameters
    Modifier and Type | Method and Description
    --- | ---
    `static TokenizerModel` | TokenizerME.`train(ObjectStream<TokenSample> samples, TokenizerFactory factory, TrainingParameters mlParams)` Trains a model for the `TokenizerME`.

    Constructors in opennlp.tools.tokenize with parameters of type TrainingParameters
    Constructor and Description
    `TokenizerCrossValidator(TrainingParameters params, TokenizerFactory factory, TokenizerEvaluationMonitor... listeners)`

  - ### Uses of TrainingParameters in opennlp.tools.util

    Methods in opennlp.tools.util that return TrainingParameters
    Modifier and Type | Method and Description
    --- | ---
    `static TrainingParameters` | TrainingParameters.`defaultParams()`
    `TrainingParameters` | TrainingParameters.`getParameters(String namespace)`

    Constructors in opennlp.tools.util with parameters of type TrainingParameters
    Constructor and Description
    `TrainingParameters(TrainingParameters trainingParameters)`

  - ### Uses of TrainingParameters in opennlp.tools.util.model

    Methods in opennlp.tools.util.model that return TrainingParameters
    Modifier and Type | Method and Description
    --- | ---
    `static TrainingParameters` | ModelUtil.`createDefaultTrainingParameters()` Creates the default training parameters in case they are not provided.

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