c

com.johnsnowlabs.nlp

AnnotatorApproach

abstract class AnnotatorApproach[M <: Model[M]] extends Estimator[M] with HasInputAnnotationCols with HasOutputAnnotationCol with HasOutputAnnotatorType with DefaultParamsWritable with CanBeLazy

This class should grow once we start training on datasets and share params For now it stands as a dummy placeholder for future reference

Linear Supertypes
CanBeLazy, DefaultParamsWritable, MLWritable, HasOutputAnnotatorType, HasOutputAnnotationCol, HasInputAnnotationCols, Estimator[M], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. AnnotatorApproach
  2. CanBeLazy
  3. DefaultParamsWritable
  4. MLWritable
  5. HasOutputAnnotatorType
  6. HasOutputAnnotationCol
  7. HasInputAnnotationCols
  8. Estimator
  9. PipelineStage
  10. Logging
  11. Params
  12. Serializable
  13. Serializable
  14. Identifiable
  15. AnyRef
  16. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new AnnotatorApproach()

Type Members

  1. type AnnotatorType = String
    Definition Classes
    HasOutputAnnotatorType

Abstract Value Members

  1. abstract val description: String
  2. abstract val inputAnnotatorTypes: Array[String]

    Annotator reference id.

    Annotator reference id. Used to identify elements in metadata or to refer to this annotator type

    Definition Classes
    HasInputAnnotationCols
  3. abstract val outputAnnotatorType: AnnotatorType
    Definition Classes
    HasOutputAnnotatorType
  4. abstract def train(dataset: Dataset[_], recursivePipeline: Option[PipelineModel] = None): M
  5. abstract val uid: String
    Definition Classes
    Identifiable

Concrete 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. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  5. def _fit(dataset: Dataset[_], recursiveStages: Option[PipelineModel]): M
    Attributes
    protected
  6. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  7. def beforeTraining(spark: SparkSession): Unit
  8. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  9. final def clear(param: Param[_]): AnnotatorApproach.this.type
    Definition Classes
    Params
  10. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  11. final def copy(extra: ParamMap): Estimator[M]
    Definition Classes
    AnnotatorApproach → Estimator → PipelineStage → Params
  12. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  13. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  14. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  15. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  16. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  17. def explainParams(): String
    Definition Classes
    Params
  18. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  19. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  20. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  21. final def fit(dataset: Dataset[_]): M
    Definition Classes
    AnnotatorApproach → Estimator
  22. def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[M]
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  23. def fit(dataset: Dataset[_], paramMap: ParamMap): M
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  24. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): M
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()
  25. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  26. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  27. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  28. def getInputCols: Array[String]

    returns

    input annotations columns currently used

    Definition Classes
    HasInputAnnotationCols
  29. def getLazyAnnotator: Boolean
    Definition Classes
    CanBeLazy
  30. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  31. final def getOutputCol: String

    Gets annotation column name going to generate

    Gets annotation column name going to generate

    Definition Classes
    HasOutputAnnotationCol
  32. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  33. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  34. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  35. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  36. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  37. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  38. final val inputCols: StringArrayParam

    columns that contain annotations necessary to run this annotator AnnotatorType is used both as input and output columns if not specified

    columns that contain annotations necessary to run this annotator AnnotatorType is used both as input and output columns if not specified

    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  39. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  40. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  41. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  42. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  43. val lazyAnnotator: BooleanParam
    Definition Classes
    CanBeLazy
  44. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  45. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  46. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  47. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  48. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  49. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  50. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  51. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  52. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  53. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  54. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  55. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  56. def msgHelper(schema: StructType): String
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  57. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  58. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  59. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  60. def onTrained(model: M, spark: SparkSession): Unit
  61. val optionalInputAnnotatorTypes: Array[String]
    Definition Classes
    HasInputAnnotationCols
  62. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  63. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  64. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  65. final def set(paramPair: ParamPair[_]): AnnotatorApproach.this.type
    Attributes
    protected
    Definition Classes
    Params
  66. final def set(param: String, value: Any): AnnotatorApproach.this.type
    Attributes
    protected
    Definition Classes
    Params
  67. final def set[T](param: Param[T], value: T): AnnotatorApproach.this.type
    Definition Classes
    Params
  68. final def setDefault(paramPairs: ParamPair[_]*): AnnotatorApproach.this.type
    Attributes
    protected
    Definition Classes
    Params
  69. final def setDefault[T](param: Param[T], value: T): AnnotatorApproach.this.type
    Attributes
    protected
    Definition Classes
    Params
  70. final def setInputCols(value: String*): AnnotatorApproach.this.type
    Definition Classes
    HasInputAnnotationCols
  71. final def setInputCols(value: Array[String]): AnnotatorApproach.this.type

    Overrides required annotators column if different than default

    Overrides required annotators column if different than default

    Definition Classes
    HasInputAnnotationCols
  72. def setLazyAnnotator(value: Boolean): AnnotatorApproach.this.type
    Definition Classes
    CanBeLazy
  73. final def setOutputCol(value: String): AnnotatorApproach.this.type

    Overrides annotation column name when transforming

    Overrides annotation column name when transforming

    Definition Classes
    HasOutputAnnotationCol
  74. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  75. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  76. final def transformSchema(schema: StructType): StructType

    requirement for pipeline transformation validation.

    requirement for pipeline transformation validation. It is called on fit()

    Definition Classes
    AnnotatorApproach → PipelineStage
  77. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  78. def validate(schema: StructType): Boolean

    takes a Dataset and checks to see if all the required annotation types are present.

    takes a Dataset and checks to see if all the required annotation types are present.

    schema

    to be validated

    returns

    True if all the required types are present, else false

    Attributes
    protected
  79. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  80. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  81. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  82. def write: MLWriter
    Definition Classes
    DefaultParamsWritable → MLWritable

Inherited from CanBeLazy

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from HasOutputAnnotatorType

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from Estimator[M]

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

Ungrouped