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c

com.johnsnowlabs.ml.tensorflow

TensorflowMedicalNer

class TensorflowMedicalNer extends Serializable with Logging

Linear Supertypes
Logging, Serializable, Serializable, AnyRef, Any
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Inherited
  1. TensorflowMedicalNer
  2. Logging
  3. Serializable
  4. Serializable
  5. AnyRef
  6. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new TensorflowMedicalNer(tensorflow: TensorflowWrapper, encoder: MedicalNerDatasetEncoder, verboseLevel: nlp.annotators.ner.Verbose.Value)

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  5. def calcStat(tp: Int, fp: Int, fn: Int): (Float, Float, Float)
  6. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  7. val encoder: MedicalNerDatasetEncoder
  8. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  9. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  10. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  11. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  12. def getInputDims: (Integer, Integer, Integer)
  13. def getLogName: String
    Definition Classes
    TensorflowMedicalNer → Logging
  14. def getPiecesTags(tokenTags: Array[TextSentenceLabels], sentences: Array[WordpieceEmbeddingsSentence]): Array[Array[String]]
  15. def getPiecesTags(tokenTags: TextSentenceLabels, sentence: WordpieceEmbeddingsSentence): Array[String]
  16. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  17. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  18. def log(value: ⇒ String, minLevel: Level): Unit
    Attributes
    protected
    Definition Classes
    Logging
  19. val logger: Logger
    Attributes
    protected
    Definition Classes
    Logging
  20. def measure(labeled: Iterator[Array[(TextSentenceLabels, WordpieceEmbeddingsSentence)]], extended: Boolean = false, includeConfidence: Boolean = false, includeAllConfidenceScores: Boolean = false, enableOutputLogs: Boolean = false, outputLogsPath: String, uuid: String = Identifiable.randomUID("annotator")): Unit
  21. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  22. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  23. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  24. def outputLog(value: ⇒ String, uuid: String, shouldLog: Boolean, outputLogsPath: String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  25. def predict(dataset: Array[WordpieceEmbeddingsSentence], configProtoBytes: Option[Array[Byte]] = None, includeConfidence: Boolean = false, includeAllConfidenceScores: Boolean = false, batchSize: Int = 1): Array[Array[(String, Option[Array[Map[String, String]]])]]
  26. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  27. def tagsForTokens(labels: Array[Array[(String, Option[Array[Map[String, String]]])]], pieces: Array[WordpieceEmbeddingsSentence]): Array[Array[(String, Option[Array[Map[String, String]]])]]
  28. def tagsForTokens(labels: Array[(String, Option[Array[Map[String, String]]])], pieces: WordpieceEmbeddingsSentence): Array[(String, Option[Array[Map[String, String]]])]
  29. val tensorflow: TensorflowWrapper
  30. def toString(): String
    Definition Classes
    AnyRef → Any
  31. def train(trainDataset: ⇒ Iterator[Array[(TextSentenceLabels, WordpieceEmbeddingsSentence)]], trainLength: Long, validDataset: ⇒ Iterator[Array[(TextSentenceLabels, WordpieceEmbeddingsSentence)]], validLength: Long, lr: Float, po: Float, dropout: Float, startEpoch: Int = 0, isPretrained: Boolean = false, endEpoch: Int, graphFileName: String = "", test: ⇒ Iterator[Array[(TextSentenceLabels, WordpieceEmbeddingsSentence)]] = Iterator.empty, configProtoBytes: Option[Array[Byte]] = None, validationSplit: Float = 0.0f, evaluationLogExtended: Boolean = false, includeConfidence: Boolean = false, includeAllConfidenceScores: Boolean = false, enableOutputLogs: Boolean = false, outputLogsPath: String, uuid: String = Identifiable.randomUID("annotator"), batchSize: Int): Unit
  32. val verboseLevel: nlp.annotators.ner.Verbose.Value
    Definition Classes
    TensorflowMedicalNer → Logging
  33. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  34. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  35. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()

Inherited from Logging

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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