object MedicalNerModel extends ReadablePretrainedMedicalNer with ReadsMedicalNerGraph with Serializable

Linear Supertypes
Serializable, Serializable, ReadsMedicalNerGraph, ReadTensorflowModel, ReadablePretrainedMedicalNer, HasPretrained[MedicalNerModel], ParamsAndFeaturesReadable[MedicalNerModel], DefaultParamsReadable[MedicalNerModel], MLReadable[MedicalNerModel], AnyRef, Any
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Inherited
  1. MedicalNerModel
  2. Serializable
  3. Serializable
  4. ReadsMedicalNerGraph
  5. ReadTensorflowModel
  6. ReadablePretrainedMedicalNer
  7. HasPretrained
  8. ParamsAndFeaturesReadable
  9. DefaultParamsReadable
  10. MLReadable
  11. AnyRef
  12. Any
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Visibility
  1. Public
  2. All

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. def addReader(reader: (MedicalNerModel, String, SparkSession) ⇒ Unit): Unit
    Definition Classes
    ParamsAndFeaturesReadable
  5. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  6. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  7. val defaultLang: String
    Definition Classes
    HasPretrained
  8. lazy val defaultLoc: String
    Definition Classes
    ReadablePretrainedMedicalNer → HasPretrained
  9. val defaultModelName: Some[String]
    Definition Classes
    ReadablePretrainedMedicalNer → HasPretrained
  10. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  11. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  12. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  13. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  14. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  15. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  16. def load(path: String): MedicalNerModel
    Definition Classes
    MLReadable
    Annotations
    @Since( "1.6.0" )
  17. def loadSavedModel(nerDLModelPath: String, amendedTfPath: String, spark: SparkSession): MedicalNerModel
  18. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  19. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  20. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  21. def pretrained(name: String, lang: String, remoteLoc: String): MedicalNerModel
    Definition Classes
    ReadablePretrainedMedicalNer → HasPretrained
  22. def pretrained(name: String, lang: String): MedicalNerModel
    Definition Classes
    ReadablePretrainedMedicalNer → HasPretrained
  23. def pretrained(name: String): MedicalNerModel
    Definition Classes
    ReadablePretrainedMedicalNer → HasPretrained
  24. def pretrained(): MedicalNerModel

    Java compliant-overrides

    Java compliant-overrides

    Definition Classes
    ReadablePretrainedMedicalNer → HasPretrained
  25. def read: MLReader[MedicalNerModel]
    Definition Classes
    ParamsAndFeaturesReadable → DefaultParamsReadable → MLReadable
  26. def readNerGraph(instance: MedicalNerModel, path: String, spark: SparkSession): Unit
    Definition Classes
    ReadsMedicalNerGraph
  27. def readTensorflowChkPoints(path: String, spark: SparkSession, suffix: String, zipped: Boolean, tags: Array[String], initAllTables: Boolean): TensorflowWrapper
    Definition Classes
    ReadTensorflowModel
  28. def readTensorflowHub(path: String, spark: SparkSession, suffix: String, zipped: Boolean, useBundle: Boolean, tags: Array[String]): TensorflowWrapper
    Definition Classes
    ReadTensorflowModel
  29. def readTensorflowModel(path: String, spark: SparkSession, suffix: String, zipped: Boolean, useBundle: Boolean, tags: Array[String], initAllTables: Boolean, savedSignatures: Option[Map[String, String]]): TensorflowWrapper
    Definition Classes
    ReadTensorflowModel
  30. def readTensorflowWithSPModel(path: String, spark: SparkSession, suffix: String, zipped: Boolean, useBundle: Boolean, tags: Array[String], initAllTables: Boolean, loadSP: Boolean): TensorflowWrapper
    Definition Classes
    ReadTensorflowModel
  31. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  32. val tfFile: String
    Definition Classes
    ReadsMedicalNerGraph → ReadTensorflowModel
  33. def toString(): String
    Definition Classes
    AnyRef → Any
  34. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  35. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  36. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()

Inherited from Serializable

Inherited from Serializable

Inherited from ReadsMedicalNerGraph

Inherited from ReadTensorflowModel

Inherited from HasPretrained[MedicalNerModel]

Inherited from ParamsAndFeaturesReadable[MedicalNerModel]

Inherited from DefaultParamsReadable[MedicalNerModel]

Inherited from MLReadable[MedicalNerModel]

Inherited from AnyRef

Inherited from Any

Ungrouped