class MedicalNerModel extends AnnotatorModel[MedicalNerModel] with HasBatchedAnnotate[MedicalNerModel] with WriteTensorflowModel with HasStorageRef with ParamsAndFeaturesWritable with CheckLicense

Linear Supertypes
CheckLicense, HasStorageRef, WriteTensorflowModel, HasBatchedAnnotate[MedicalNerModel], AnnotatorModel[MedicalNerModel], CanBeLazy, RawAnnotator[MedicalNerModel], HasOutputAnnotationCol, HasInputAnnotationCols, HasOutputAnnotatorType, ParamsAndFeaturesWritable, HasFeatures, DefaultParamsWritable, MLWritable, Model[MedicalNerModel], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. MedicalNerModel
  2. CheckLicense
  3. HasStorageRef
  4. WriteTensorflowModel
  5. HasBatchedAnnotate
  6. AnnotatorModel
  7. CanBeLazy
  8. RawAnnotator
  9. HasOutputAnnotationCol
  10. HasInputAnnotationCols
  11. HasOutputAnnotatorType
  12. ParamsAndFeaturesWritable
  13. HasFeatures
  14. DefaultParamsWritable
  15. MLWritable
  16. Model
  17. Transformer
  18. PipelineStage
  19. Logging
  20. Params
  21. Serializable
  22. Serializable
  23. Identifiable
  24. AnyRef
  25. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new MedicalNerModel()
  2. new MedicalNerModel(uid: String)

Type Members

  1. type AnnotationContent = Seq[Row]
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  2. type AnnotatorType = String
    Definition Classes
    HasOutputAnnotatorType

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def $[T](param: Param[T]): T
    Attributes
    protected
    Definition Classes
    Params
  4. def $$[T](feature: StructFeature[T]): T
    Attributes
    protected
    Definition Classes
    HasFeatures
  5. def $$[K, V](feature: MapFeature[K, V]): Map[K, V]
    Attributes
    protected
    Definition Classes
    HasFeatures
  6. def $$[T](feature: SetFeature[T]): Set[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  7. def $$[T](feature: ArrayFeature[T]): Array[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  8. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  9. def _transform(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): DataFrame
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  10. def afterAnnotate(dataset: DataFrame): DataFrame
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  11. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  12. def batchAnnotate(batchedAnnotations: Seq[Array[Annotation]]): Seq[Seq[Annotation]]
    Definition Classes
    MedicalNerModel → HasBatchedAnnotate
  13. def batchProcess(rows: Iterator[_]): Iterator[Row]
    Definition Classes
    HasBatchedAnnotate
  14. val batchSize: IntParam
    Definition Classes
    HasBatchedAnnotate
  15. def beforeAnnotate(dataset: Dataset[_]): Dataset[_]
    Attributes
    protected
    Definition Classes
    MedicalNerModel → AnnotatorModel
  16. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  17. def checkValidEnvironment(spark: Option[SparkSession]): Unit
    Definition Classes
    CheckLicense
  18. def checkValidScope(scope: String): Unit
    Definition Classes
    CheckLicense
  19. def checkValidScopeAndEnvironment(scope: String, spark: Option[SparkSession], checkLp: Boolean): Unit
    Definition Classes
    CheckLicense
  20. def checkValidScopesAndEnvironment(scopes: Seq[String], spark: Option[SparkSession], checkLp: Boolean): Unit
    Definition Classes
    CheckLicense
  21. val classes: StringArrayParam
  22. final def clear(param: Param[_]): MedicalNerModel.this.type
    Definition Classes
    Params
  23. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  24. val configProtoBytes: IntArrayParam

    ConfigProto from tensorflow, serialized into byte array.

    ConfigProto from tensorflow, serialized into byte array. Get with config_proto.SerializeToString()

  25. def copy(extra: ParamMap): MedicalNerModel
    Definition Classes
    RawAnnotator → Model → Transformer → PipelineStage → Params
  26. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  27. def createDatabaseConnection(database: Name): RocksDBConnection
    Definition Classes
    HasStorageRef
  28. val datasetParams: StructFeature[DatasetEncoderParams]

    datasetParams

  29. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  30. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  31. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  32. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  33. def explainParams(): String
    Definition Classes
    Params
  34. def extraValidate(structType: StructType): Boolean
    Attributes
    protected
    Definition Classes
    RawAnnotator
  35. def extraValidateMsg: String
    Attributes
    protected
    Definition Classes
    RawAnnotator
  36. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  37. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  38. val features: ArrayBuffer[Feature[_, _, _]]
    Definition Classes
    HasFeatures
  39. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  40. def get[T](feature: StructFeature[T]): Option[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  41. def get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  42. def get[T](feature: SetFeature[T]): Option[Set[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  43. def get[T](feature: ArrayFeature[T]): Option[Array[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  44. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  45. def getBatchSize: Int
    Definition Classes
    HasBatchedAnnotate
  46. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  47. def getClasses: Array[String]

    get the tags used to trained this MedicalNerModel

  48. def getConfigProtoBytes: Option[Array[Byte]]

    datasetParams

  49. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  50. def getIncludeAllConfidenceScores: Boolean

    whether to include all confidence scores in annotation metadata or just the score of the predicted tag

  51. def getIncludeConfidence: Boolean

    whether to include confidence scores in annotation metadata

  52. def getInferenceBatchSize: Int

    get the number of sentences to process in a single batch during inference

  53. def getInputCols: Array[String]
    Definition Classes
    HasInputAnnotationCols
  54. def getLazyAnnotator: Boolean
    Definition Classes
    CanBeLazy
  55. def getMinProba: Float

    Minimum probability.

    Minimum probability. Used only if there is no CRF on top of LSTM layer.

  56. def getModelIfNotSet: TensorflowMedicalNer

    ConfigProto from tensorflow, serialized into byte array.

    ConfigProto from tensorflow, serialized into byte array. Get with config_proto.SerializeToString()

  57. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  58. final def getOutputCol: String
    Definition Classes
    HasOutputAnnotationCol
  59. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  60. def getStorageRef: String
    Definition Classes
    HasStorageRef
  61. def getTrainingClassDistribution: Map[String, Long]
  62. def getTrainingClassDistributionJava: Map[String, Long]
  63. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  64. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  65. def hasParent: Boolean
    Definition Classes
    Model
  66. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  67. val includeAllConfidenceScores: BooleanParam

    whether to include all confidence scores in annotation metadata or just score of the predicted tag

  68. val includeConfidence: BooleanParam

    whether to include confidence scores in annotation metadata

  69. val inferenceBatchSize: IntParam

    Number of sentences to process in a single batch during inference

  70. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  71. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  72. val inputAnnotatorTypes: Array[String]

    Required input Annotators coulumns, expects DOCUMENT, TOKEN, WORD_EMBEDDINGS

    Required input Annotators coulumns, expects DOCUMENT, TOKEN, WORD_EMBEDDINGS

    Definition Classes
    MedicalNerModel → HasInputAnnotationCols
  73. final val inputCols: StringArrayParam
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  74. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  75. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  76. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  77. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  78. val labelCasing: Param[String]

    Set the tag to case sensitive or not.Setting all labels of the NER models upper/lower case.

    Set the tag to case sensitive or not.Setting all labels of the NER models upper/lower case. values upper|lower

  79. val lazyAnnotator: BooleanParam
    Definition Classes
    CanBeLazy
  80. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  81. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  82. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  83. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  84. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  85. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  86. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  87. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  88. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  89. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  90. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  91. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  92. val minProba: FloatParam

    Minimum probability.

    Minimum probability. Used only if there is no CRF on top of LSTM layer.

  93. def msgHelper(schema: StructType): String
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  94. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  95. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  96. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  97. def onWrite(path: String, spark: SparkSession): Unit
    Definition Classes
    MedicalNerModel → ParamsAndFeaturesWritable
  98. val optionalInputAnnotatorTypes: Array[String]
    Definition Classes
    HasInputAnnotationCols
  99. val outputAnnotatorType: String

    Output Annnotator type : NAMED_ENTITY

    Output Annnotator type : NAMED_ENTITY

    Definition Classes
    MedicalNerModel → HasOutputAnnotatorType
  100. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  101. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  102. var parent: Estimator[MedicalNerModel]
    Definition Classes
    Model
  103. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  104. def set[T](feature: StructFeature[T], value: T): MedicalNerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  105. def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): MedicalNerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  106. def set[T](feature: SetFeature[T], value: Set[T]): MedicalNerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  107. def set[T](feature: ArrayFeature[T], value: Array[T]): MedicalNerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  108. final def set(paramPair: ParamPair[_]): MedicalNerModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  109. final def set(param: String, value: Any): MedicalNerModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  110. final def set[T](param: Param[T], value: T): MedicalNerModel.this.type
    Definition Classes
    Params
  111. def setBatchSize(size: Int): MedicalNerModel.this.type
    Definition Classes
    HasBatchedAnnotate
  112. def setConfigProtoBytes(bytes: Array[Int]): MedicalNerModel.this.type

    ConfigProto from tensorflow, serialized into byte array.

    ConfigProto from tensorflow, serialized into byte array. Get with config_proto.SerializeToString()

  113. def setDatasetParams(params: DatasetEncoderParams): MedicalNerModel.this.type

    datasetParams

  114. def setDefault[T](feature: StructFeature[T], value: () ⇒ T): MedicalNerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  115. def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): MedicalNerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  116. def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): MedicalNerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  117. def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): MedicalNerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  118. final def setDefault(paramPairs: ParamPair[_]*): MedicalNerModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  119. final def setDefault[T](param: Param[T], value: T): MedicalNerModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  120. def setIncludeAllConfidenceScores(value: Boolean): MedicalNerModel.this.type

    whether to include confidence scores for all tags rather than just for the predicted one

  121. def setIncludeConfidence(value: Boolean): MedicalNerModel.this.type

    whether to include confidence scores in annotation metadata

  122. def setInferenceBatchSize(value: Int): MedicalNerModel.this.type

    set the number of sentences to process in a single batch during inference

  123. final def setInputCols(value: String*): MedicalNerModel.this.type
    Definition Classes
    HasInputAnnotationCols
  124. def setInputCols(value: Array[String]): MedicalNerModel.this.type
    Definition Classes
    HasInputAnnotationCols
  125. def setLabelCasing(value: String): MedicalNerModel.this.type
  126. def setLazyAnnotator(value: Boolean): MedicalNerModel.this.type
    Definition Classes
    CanBeLazy
  127. def setMinProbability(minProba: Float): MedicalNerModel.this.type

    Minimum probability.

    Minimum probability. Used only if there is no CRF on top of LSTM layer.

  128. def setModelIfNotSet(spark: SparkSession, tf: TensorflowWrapper): MedicalNerModel.this.type
  129. final def setOutputCol(value: String): MedicalNerModel.this.type
    Definition Classes
    HasOutputAnnotationCol
  130. def setParent(parent: Estimator[MedicalNerModel]): MedicalNerModel
    Definition Classes
    Model
  131. def setStorageRef(value: String): MedicalNerModel.this.type
    Definition Classes
    HasStorageRef
  132. def setTrainingClassDistribution(value: Map[String, Long]): MedicalNerModel.this.type

    set the number of sentences to process in a single batch during inference

  133. val storageRef: Param[String]
    Definition Classes
    HasStorageRef
  134. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  135. def tag(tokenized: Array[Array[WordpieceEmbeddingsSentence]]): Seq[Array[NerTaggedSentence]]
  136. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  137. val trainingClassDistribution: MapFeature[String, Long]
  138. final def transform(dataset: Dataset[_]): DataFrame
    Definition Classes
    AnnotatorModel → Transformer
  139. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  140. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  141. final def transformSchema(schema: StructType): StructType
    Definition Classes
    RawAnnotator → PipelineStage
  142. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  143. val uid: String
    Definition Classes
    MedicalNerModel → Identifiable
  144. def validate(schema: StructType): Boolean
    Attributes
    protected
    Definition Classes
    RawAnnotator
  145. def validateStorageRef(dataset: Dataset[_], inputCols: Array[String], annotatorType: String): Unit
    Definition Classes
    HasStorageRef
  146. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  147. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  148. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  149. def wrapColumnMetadata(col: Column): Column
    Attributes
    protected
    Definition Classes
    RawAnnotator
  150. def write: MLWriter
    Definition Classes
    ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable
  151. def writeTensorflowHub(path: String, tfPath: String, spark: SparkSession, suffix: String): Unit
    Definition Classes
    WriteTensorflowModel
  152. def writeTensorflowModel(path: String, spark: SparkSession, tensorflow: TensorflowWrapper, suffix: String, filename: String, configProtoBytes: Option[Array[Byte]]): Unit
    Definition Classes
    WriteTensorflowModel
  153. def writeTensorflowModelV2(path: String, spark: SparkSession, tensorflow: TensorflowWrapper, suffix: String, filename: String, configProtoBytes: Option[Array[Byte]], savedSignatures: Option[Map[String, String]]): Unit
    Definition Classes
    WriteTensorflowModel

Inherited from CheckLicense

Inherited from HasStorageRef

Inherited from WriteTensorflowModel

Inherited from HasBatchedAnnotate[MedicalNerModel]

Inherited from AnnotatorModel[MedicalNerModel]

Inherited from CanBeLazy

Inherited from RawAnnotator[MedicalNerModel]

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from HasOutputAnnotatorType

Inherited from ParamsAndFeaturesWritable

Inherited from HasFeatures

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from Model[MedicalNerModel]

Inherited from Transformer

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

anno

getParam

param

setParam

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