Class

com.johnsnowlabs.nlp.annotators.classifier.dl

ClassifierDLApproach

Related Doc: package dl

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class ClassifierDLApproach extends AnnotatorApproach[ClassifierDLModel] with ParamsAndFeaturesWritable

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

Instance Constructors

  1. new ClassifierDLApproach()

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  2. new ClassifierDLApproach(uid: String)

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Type Members

  1. type AnnotatorType = String

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    Definition Classes
    HasOutputAnnotatorType

Value Members

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

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    Definition Classes
    AnyRef → Any
  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any
  3. final def $[T](param: Param[T]): T

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    Attributes
    protected
    Definition Classes
    Params
  4. def $$[T](feature: StructFeature[T]): T

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    Attributes
    protected
    Definition Classes
    HasFeatures
  5. def $$[K, V](feature: MapFeature[K, V]): Map[K, V]

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    Attributes
    protected
    Definition Classes
    HasFeatures
  6. def $$[T](feature: SetFeature[T]): Set[T]

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    Attributes
    protected
    Definition Classes
    HasFeatures
  7. def $$[T](feature: ArrayFeature[T]): Array[T]

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    Attributes
    protected
    Definition Classes
    HasFeatures
  8. final def ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  9. def _fit(dataset: Dataset[_], recursiveStages: Option[PipelineModel]): ClassifierDLModel

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    Attributes
    protected
    Definition Classes
    AnnotatorApproach
  10. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any
  11. val batchSize: IntParam

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  12. def beforeTraining(spark: SparkSession): Unit

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

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    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  14. final def clear(param: Param[_]): ClassifierDLApproach.this.type

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    Definition Classes
    Params
  15. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  16. val configProtoBytes: IntArrayParam

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  17. final def copy(extra: ParamMap): Estimator[ClassifierDLModel]

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    Definition Classes
    AnnotatorApproach → Estimator → PipelineStage → Params
  18. def copyValues[T <: Params](to: T, extra: ParamMap): T

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    Attributes
    protected
    Definition Classes
    Params
  19. final def defaultCopy[T <: Params](extra: ParamMap): T

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    Attributes
    protected
    Definition Classes
    Params
  20. val description: String

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  21. val dropout: FloatParam

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  22. val enableOutputLogs: BooleanParam

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

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    Definition Classes
    AnyRef
  24. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  25. def explainParam(param: Param[_]): String

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    Definition Classes
    Params
  26. def explainParams(): String

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    Definition Classes
    Params
  27. final def extractParamMap(): ParamMap

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    Definition Classes
    Params
  28. final def extractParamMap(extra: ParamMap): ParamMap

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    Definition Classes
    Params
  29. val features: ArrayBuffer[Feature[_, _, _]]

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    Definition Classes
    HasFeatures
  30. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  31. final def fit(dataset: Dataset[_]): ClassifierDLModel

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    Definition Classes
    AnnotatorApproach → Estimator
  32. def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[ClassifierDLModel]

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  33. def fit(dataset: Dataset[_], paramMap: ParamMap): ClassifierDLModel

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  34. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): ClassifierDLModel

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()
  35. def get[T](feature: StructFeature[T]): Option[T]

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    Attributes
    protected
    Definition Classes
    HasFeatures
  36. def get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]

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    Attributes
    protected
    Definition Classes
    HasFeatures
  37. def get[T](feature: SetFeature[T]): Option[Set[T]]

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    Attributes
    protected
    Definition Classes
    HasFeatures
  38. def get[T](feature: ArrayFeature[T]): Option[Array[T]]

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    Attributes
    protected
    Definition Classes
    HasFeatures
  39. final def get[T](param: Param[T]): Option[T]

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    Definition Classes
    Params
  40. def getBatchSize: Int

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

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    Definition Classes
    AnyRef → Any
  42. def getConfigProtoBytes: Option[Array[Byte]]

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

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    Definition Classes
    Params
  44. def getDropout: Float

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  45. def getEnableOutputLogs: Boolean

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  46. def getInputCols: Array[String]

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    returns

    input annotations columns currently used

    Definition Classes
    HasInputAnnotationCols
  47. def getLabelColumn: String

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  48. def getLazyAnnotator: Boolean

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    Definition Classes
    CanBeLazy
  49. def getLr: Float

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  50. def getMaxEpochs: Int

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

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    Definition Classes
    Params
  52. final def getOutputCol: String

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    Gets annotation column name going to generate

    Gets annotation column name going to generate

    Definition Classes
    HasOutputAnnotationCol
  53. def getParam(paramName: String): Param[Any]

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    Definition Classes
    Params
  54. def getValidationSplit: Float

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

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    Definition Classes
    Params
  56. def hasParam(paramName: String): Boolean

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    Definition Classes
    Params
  57. def hashCode(): Int

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    Definition Classes
    AnyRef → Any
  58. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

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    Attributes
    protected
    Definition Classes
    Logging
  59. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  60. val inputAnnotatorTypes: Array[AnnotatorType]

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    Annotator reference id.

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

    Definition Classes
    ClassifierDLApproachHasInputAnnotationCols
  61. final val inputCols: StringArrayParam

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

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    Definition Classes
    Params
  63. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any
  64. final def isSet(param: Param[_]): Boolean

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    Definition Classes
    Params
  65. def isTraceEnabled(): Boolean

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    Attributes
    protected
    Definition Classes
    Logging
  66. val labelColumn: Param[String]

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  67. val lazyAnnotator: BooleanParam

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    Definition Classes
    CanBeLazy
  68. def loadSavedModel(): TensorflowWrapper

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  69. def log: Logger

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    Attributes
    protected
    Definition Classes
    Logging
  70. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  71. def logDebug(msg: ⇒ String): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  72. def logError(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  73. def logError(msg: ⇒ String): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  74. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  75. def logInfo(msg: ⇒ String): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  76. def logName: String

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    Attributes
    protected
    Definition Classes
    Logging
  77. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  78. def logTrace(msg: ⇒ String): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  79. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  80. def logWarning(msg: ⇒ String): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  81. val lr: FloatParam

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  82. val maxEpochs: IntParam

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  83. def msgHelper(schema: StructType): String

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    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  84. final def ne(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  85. final def notify(): Unit

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    Definition Classes
    AnyRef
  86. final def notifyAll(): Unit

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    Definition Classes
    AnyRef
  87. def onTrained(model: ClassifierDLModel, spark: SparkSession): Unit

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    Definition Classes
    AnnotatorApproach
  88. def onWrite(path: String, spark: SparkSession): Unit

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    Attributes
    protected
    Definition Classes
    ParamsAndFeaturesWritable
  89. val outputAnnotatorType: String

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  90. final val outputCol: Param[String]

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    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  91. lazy val params: Array[Param[_]]

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    Definition Classes
    Params
  92. val randomSeed: IntParam

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  93. def save(path: String): Unit

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    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  94. def set[T](feature: StructFeature[T], value: T): ClassifierDLApproach.this.type

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    Attributes
    protected
    Definition Classes
    HasFeatures
  95. def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): ClassifierDLApproach.this.type

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    Attributes
    protected
    Definition Classes
    HasFeatures
  96. def set[T](feature: SetFeature[T], value: Set[T]): ClassifierDLApproach.this.type

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    Attributes
    protected
    Definition Classes
    HasFeatures
  97. def set[T](feature: ArrayFeature[T], value: Array[T]): ClassifierDLApproach.this.type

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    Attributes
    protected
    Definition Classes
    HasFeatures
  98. final def set(paramPair: ParamPair[_]): ClassifierDLApproach.this.type

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    Attributes
    protected
    Definition Classes
    Params
  99. final def set(param: String, value: Any): ClassifierDLApproach.this.type

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    Attributes
    protected
    Definition Classes
    Params
  100. final def set[T](param: Param[T], value: T): ClassifierDLApproach.this.type

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    Definition Classes
    Params
  101. def setBatchSize(batch: Int): ClassifierDLApproach.this.type

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  102. def setConfigProtoBytes(bytes: Array[Int]): ClassifierDLApproach.this.type

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  103. def setDefault[T](feature: StructFeature[T], value: () ⇒ T): ClassifierDLApproach.this.type

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    Attributes
    protected
    Definition Classes
    HasFeatures
  104. def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): ClassifierDLApproach.this.type

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    Attributes
    protected
    Definition Classes
    HasFeatures
  105. def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): ClassifierDLApproach.this.type

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    Attributes
    protected
    Definition Classes
    HasFeatures
  106. def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): ClassifierDLApproach.this.type

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    Attributes
    protected
    Definition Classes
    HasFeatures
  107. final def setDefault(paramPairs: ParamPair[_]*): ClassifierDLApproach.this.type

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    Attributes
    protected
    Definition Classes
    Params
  108. final def setDefault[T](param: Param[T], value: T): ClassifierDLApproach.this.type

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    Attributes
    protected
    Definition Classes
    Params
  109. def setDropout(dropout: Float): ClassifierDLApproach.this.type

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  110. def setEnableOutputLogs(enableOutputLogs: Boolean): ClassifierDLApproach.this.type

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  111. final def setInputCols(value: String*): ClassifierDLApproach.this.type

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    Definition Classes
    HasInputAnnotationCols
  112. final def setInputCols(value: Array[String]): ClassifierDLApproach.this.type

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    Overrides required annotators column if different than default

    Overrides required annotators column if different than default

    Definition Classes
    HasInputAnnotationCols
  113. def setLabelColumn(column: String): ClassifierDLApproach.this.type

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  114. def setLazyAnnotator(value: Boolean): ClassifierDLApproach.this.type

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    Definition Classes
    CanBeLazy
  115. def setLr(lr: Float): ClassifierDLApproach.this.type

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  116. def setMaxEpochs(epochs: Int): ClassifierDLApproach.this.type

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  117. final def setOutputCol(value: String): ClassifierDLApproach.this.type

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    Overrides annotation column name when transforming

    Overrides annotation column name when transforming

    Definition Classes
    HasOutputAnnotationCol
  118. def setValidationSplit(validationSplit: Float): ClassifierDLApproach.this.type

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  119. def setVerbose(verbose: Level): ClassifierDLApproach.this.type

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  120. def setVerbose(verbose: Int): ClassifierDLApproach.this.type

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

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    Definition Classes
    AnyRef
  122. def toString(): String

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    Definition Classes
    Identifiable → AnyRef → Any
  123. def train(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): ClassifierDLModel

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  124. final def transformSchema(schema: StructType): StructType

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    requirement for pipeline transformation validation.

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

    Definition Classes
    AnnotatorApproach → PipelineStage
  125. def transformSchema(schema: StructType, logging: Boolean): StructType

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    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  126. val uid: String

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    Definition Classes
    ClassifierDLApproach → Identifiable
  127. def validate(schema: StructType): Boolean

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    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
  128. val validationSplit: FloatParam

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  129. val verbose: IntParam

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  130. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  131. final def wait(arg0: Long, arg1: Int): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  132. final def wait(arg0: Long): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  133. def write: MLWriter

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    Definition Classes
    ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable

Inherited from ParamsAndFeaturesWritable

Inherited from HasFeatures

Inherited from CanBeLazy

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from HasOutputAnnotatorType

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from Estimator[ClassifierDLModel]

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