SentenceDetectorDLApproach

Value Members

1. final def !=(arg0: Any): Boolean

   

   Definition Classes

   AnyRef → Any

2. final def ##(): Int

   

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3. final def $[T](param: Param[T]): T

   

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4. final def ==(arg0: Any): Boolean

   

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   AnyRef → Any

5. def _fit(dataset: Dataset[_], recursiveStages: Option[PipelineModel]): SentenceDetectorDLModel

   

   Attributes

   protected

   Definition Classes

   AnnotatorApproach

6. final def asInstanceOf[T0]: T0

   

   Definition Classes

   Any

7. def beforeTraining(spark: SparkSession): Unit

   

   Definition Classes

   AnnotatorApproach

8. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean

   

   Attributes

   protected

   Definition Classes

   HasInputAnnotationCols

9. final def clear(param: Param[_]): SentenceDetectorDLApproach.this.type

   

   Definition Classes

   Params

10. def clone(): AnyRef

    

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    protected[java.lang]

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

11. final def copy(extra: ParamMap): Estimator[SentenceDetectorDLModel]

    

    Definition Classes

    AnnotatorApproach → Estimator → PipelineStage → Params

12. def copyValues[T <: Params](to: T, extra: ParamMap): T

    

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13. final def defaultCopy[T <: Params](extra: ParamMap): T

    

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14. val description: String

    

    Trains TensorFlow model for multi-class text classification

    Trains TensorFlow model for multi-class text classification

    Definition Classes

    SentenceDetectorDLApproach → AnnotatorApproach

15. val epochsNumber: IntParam

    

    Maximum number of epochs to train

16. final def eq(arg0: AnyRef): Boolean

    

    Definition Classes

    AnyRef

17. def equals(arg0: Any): Boolean

    

    Definition Classes

    AnyRef → Any

18. def explainParam(param: Param[_]): String

    

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    Params

19. def explainParams(): String

    

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    Params

20. final def extractParamMap(): ParamMap

    

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    Params

21. final def extractParamMap(extra: ParamMap): ParamMap

    

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    Params

22. def finalize(): Unit

    

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    protected[java.lang]

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    AnyRef

    Annotations

    @throws( classOf[java.lang.Throwable] )

23. final def fit(dataset: Dataset[_]): SentenceDetectorDLModel

    

    Definition Classes

    AnnotatorApproach → Estimator

24. def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[SentenceDetectorDLModel]

    

    Definition Classes

    Estimator

    Annotations

    @Since( "2.0.0" )

25. def fit(dataset: Dataset[_], paramMap: ParamMap): SentenceDetectorDLModel

    

    Definition Classes

    Estimator

    Annotations

    @Since( "2.0.0" )

26. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): SentenceDetectorDLModel

    

    Definition Classes

    Estimator

    Annotations

    @Since( "2.0.0" ) @varargs()

27. final def get[T](param: Param[T]): Option[T]

    

    Definition Classes

    Params

28. final def getClass(): Class[_]

    

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    AnyRef → Any

29. final def getDefault[T](param: Param[T]): Option[T]

    

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    Params

30. def getEpochsNumber: Int

    

    Maximum number of epochs to train

31. def getGraphFilename: String

    

32. def getImpossiblePenultimates: Array[String]

    

    Get impossible penultimates

33. def getInputCols: Array[String]

    
    returns

    input annotations columns currently used

    Definition Classes

    HasInputAnnotationCols

34. def getLazyAnnotator: Boolean

    

    Definition Classes

    CanBeLazy

35. def getModel: String

    

    Get model architecture

36. final def getOrDefault[T](param: Param[T]): T

    

    Definition Classes

    Params

37. final def getOutputCol: String

    

    Gets annotation column name going to generate

    Gets annotation column name going to generate

    Definition Classes

    HasOutputAnnotationCol

38. def getOutputLogsPath: String

    

    Get output logs path

39. def getParam(paramName: String): Param[Any]

    

    Definition Classes

    Params

40. def getValidationSplit: Float

    

    Choose the proportion of training dataset to be validated against the model on each Epoch.

    Choose the proportion of training dataset to be validated against the model on each Epoch. The value should be between 0.0 and 1.0 and by default it is 0.0 and off.

41. final def hasDefault[T](param: Param[T]): Boolean

    

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42. def hasParam(paramName: String): Boolean

    

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    Params

43. def hashCode(): Int

    

    Definition Classes

    AnyRef → Any

44. val impossiblePenultimates: StringArrayParam

    

    Impossible penultimates

45. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

    

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    Definition Classes

    Logging

46. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

    

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    Definition Classes

    Logging

47. val inputAnnotatorTypes: Array[AnnotatorType]

    

    Input annotator type : SENTENCE_EMBEDDINGS

    Input annotator type : SENTENCE_EMBEDDINGS

    Definition Classes

    SentenceDetectorDLApproach → HasInputAnnotationCols

48. 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

49. final def isDefined(param: Param[_]): Boolean

    

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    Params

50. final def isInstanceOf[T0]: Boolean

    

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    Any

51. final def isSet(param: Param[_]): Boolean

    

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    Params

52. def isTraceEnabled(): Boolean

    

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    Logging

53. val lazyAnnotator: BooleanParam

    

    Definition Classes

    CanBeLazy

54. def log: Logger

    

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    Logging

55. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

    

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    Logging

56. def logDebug(msg: ⇒ String): Unit

    

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    Logging

57. def logError(msg: ⇒ String, throwable: Throwable): Unit

    

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    Logging

58. def logError(msg: ⇒ String): Unit

    

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    Logging

59. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

    

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    Logging

60. def logInfo(msg: ⇒ String): Unit

    

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    Logging

61. def logName: String

    

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    Logging

62. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

    

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    Logging

63. def logTrace(msg: ⇒ String): Unit

    

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    Logging

64. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

    

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    Logging

65. def logWarning(msg: ⇒ String): Unit

    

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    Logging

66. var modelArchitecture: Param[String]

    

    Model architecture

67. def msgHelper(schema: StructType): String

    

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    protected

    Definition Classes

    HasInputAnnotationCols

68. final def ne(arg0: AnyRef): Boolean

    

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    AnyRef

69. final def notify(): Unit

    

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    AnyRef

70. final def notifyAll(): Unit

    

    Definition Classes

    AnyRef

71. def onTrained(model: SentenceDetectorDLModel, spark: SparkSession): Unit

    

    Definition Classes

    AnnotatorApproach

72. val outputAnnotatorType: String

    

    Output annotator type : CATEGORY

    Output annotator type : CATEGORY

    Definition Classes

    SentenceDetectorDLApproach → HasOutputAnnotatorType

73. final val outputCol: Param[String]

    

    Attributes

    protected

    Definition Classes

    HasOutputAnnotationCol

74. val outputLogsPath: Param[String]

    

    Path to folder to output logs.

    Path to folder to output logs. If no path is specified, no logs are generated

75. lazy val params: Array[Param[_]]

    

    Definition Classes

    Params

76. def save(path: String): Unit

    

    Definition Classes

    MLWritable

    Annotations

    @Since( "1.6.0" ) @throws( ... )

77. final def set(paramPair: ParamPair[_]): SentenceDetectorDLApproach.this.type

    

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78. final def set(param: String, value: Any): SentenceDetectorDLApproach.this.type

    

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79. final def set[T](param: Param[T], value: T): SentenceDetectorDLApproach.this.type

    

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80. final def setDefault(paramPairs: ParamPair[_]*): SentenceDetectorDLApproach.this.type

    

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81. final def setDefault[T](param: Param[T], value: T): SentenceDetectorDLApproach.this.type

    

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82. def setEpochsNumber(epochs: Int): SentenceDetectorDLApproach.this.type

    

    Maximum number of epochs to train

83. def setGraphFile(graphFilename: String): SentenceDetectorDLApproach.this.type

    

84. def setImpossiblePenultimates(impossiblePenultimates: Array[String]): SentenceDetectorDLApproach.this.type

    

    Set impossible penultimates

85. final def setInputCols(value: String*): SentenceDetectorDLApproach.this.type

    

    Definition Classes

    HasInputAnnotationCols

86. final def setInputCols(value: Array[String]): SentenceDetectorDLApproach.this.type

    

    Overrides required annotators column if different than default

    Overrides required annotators column if different than default

    Definition Classes

    HasInputAnnotationCols

87. def setLazyAnnotator(value: Boolean): SentenceDetectorDLApproach.this.type

    

    Definition Classes

    CanBeLazy

88. def setModel(modelArchitecture: String): SentenceDetectorDLApproach.this.type

    

    Set architecture

89. final def setOutputCol(value: String): SentenceDetectorDLApproach.this.type

    

    Overrides annotation column name when transforming

    Overrides annotation column name when transforming

    Definition Classes

    HasOutputAnnotationCol

90. def setOutputLogsPath(outputLogsPath: String): SentenceDetectorDLApproach.this.type

    

    Set the output log path

91. def setValidationSplit(validationSplit: Float): SentenceDetectorDLApproach.this.type

    

    Choose the proportion of training dataset to be validated against the model on each Epoch.

    Choose the proportion of training dataset to be validated against the model on each Epoch. The value should be between 0.0 and 1.0 and by default it is 0.0 and off.

92. final def synchronized[T0](arg0: ⇒ T0): T0

    

    Definition Classes

    AnyRef

93. def toString(): String

    

    Definition Classes

    Identifiable → AnyRef → Any

94. def train(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): SentenceDetectorDLModel

    

    Definition Classes

    SentenceDetectorDLApproach → AnnotatorApproach

95. 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

96. def transformSchema(schema: StructType, logging: Boolean): StructType

    

    Attributes

    protected

    Definition Classes

    PipelineStage

    Annotations

    @DeveloperApi()

97. val uid: String

    

    Definition Classes

    SentenceDetectorDLApproach → Identifiable

98. 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

    Definition Classes

    AnnotatorApproach

99. val validationSplit: FloatParam

    

    Choose the proportion of training dataset to be validated against the model on each Epoch.

    Choose the proportion of training dataset to be validated against the model on each Epoch. The value should be between 0.0 and 1.0 and by default it is 0.0 and off.

100. final def wait(): Unit

     

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     @throws( ... )

101. final def wait(arg0: Long, arg1: Int): Unit

     

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     @throws( ... )

102. final def wait(arg0: Long): Unit

     

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     AnyRef

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     @throws( ... )

103. def write: MLWriter

     

     Definition Classes

     DefaultParamsWritable → MLWritable