Class

org.apache.spark.ml.mleap.classification

SVMModel

Related Doc: package classification

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class SVMModel extends ProbabilisticClassificationModel[Vector, SVMModel] with SVMBase

Linear Supertypes
SVMBase, ProbabilisticClassificationModel[Vector, SVMModel], ProbabilisticClassifierParams, HasThresholds, HasProbabilityCol, ClassificationModel[Vector, SVMModel], ClassifierParams, HasRawPredictionCol, PredictionModel[Vector, SVMModel], PredictorParams, HasPredictionCol, HasFeaturesCol, HasLabelCol, Model[SVMModel], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. SVMModel
  2. SVMBase
  3. ProbabilisticClassificationModel
  4. ProbabilisticClassifierParams
  5. HasThresholds
  6. HasProbabilityCol
  7. ClassificationModel
  8. ClassifierParams
  9. HasRawPredictionCol
  10. PredictionModel
  11. PredictorParams
  12. HasPredictionCol
  13. HasFeaturesCol
  14. HasLabelCol
  15. Model
  16. Transformer
  17. PipelineStage
  18. Logging
  19. Params
  20. Serializable
  21. Serializable
  22. Identifiable
  23. AnyRef
  24. Any
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Visibility
  1. Public
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Instance Constructors

  1. new SVMModel(model: mllib.classification.SVMModel)

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  2. new SVMModel(uid: String, model: mllib.classification.SVMModel)

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

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    Definition Classes
    AnyRef → Any
  5. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any
  6. final def clear(param: Param[_]): SVMModel.this.type

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    Definition Classes
    Params
  7. def clearThreshold(): SVMModel.this.type

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  8. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  9. def copy(extra: ParamMap): SVMModel

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    Definition Classes
    SVMModel → Model → Transformer → PipelineStage → Params
  10. def copyValues[T <: Params](to: T, extra: ParamMap): T

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

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    Attributes
    protected
    Definition Classes
    Params
  12. final def eq(arg0: AnyRef): Boolean

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

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

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    Definition Classes
    Params
  15. def explainParams(): String

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

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

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    Definition Classes
    Params
  18. final val featuresCol: Param[String]

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    Definition Classes
    HasFeaturesCol
  19. def featuresDataType: DataType

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    Attributes
    protected
    Definition Classes
    PredictionModel
  20. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  21. final val fitIntercept: BooleanParam

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    Param for whether to fit the intercept.

    Param for whether to fit the intercept.

    Definition Classes
    SVMBase
  22. final def get[T](param: Param[T]): Option[T]

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    Definition Classes
    Params
  23. final def getClass(): Class[_]

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    Definition Classes
    AnyRef → Any
  24. final def getDefault[T](param: Param[T]): Option[T]

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    Definition Classes
    Params
  25. final def getFeaturesCol: String

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    Definition Classes
    HasFeaturesCol
  26. final def getFitIntercept: Boolean

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    Definition Classes
    SVMBase
  27. final def getLabelCol: String

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    Definition Classes
    HasLabelCol
  28. final def getMiniBatchFraction: Double

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    Definition Classes
    SVMBase
  29. final def getNumIterations: Int

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    Definition Classes
    SVMBase
  30. final def getOrDefault[T](param: Param[T]): T

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    Definition Classes
    Params
  31. def getParam(paramName: String): Param[Any]

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    Definition Classes
    Params
  32. final def getPredictionCol: String

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    Definition Classes
    HasPredictionCol
  33. final def getProbabilityCol: String

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    Definition Classes
    HasProbabilityCol
  34. final def getRawPredictionCol: String

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    Definition Classes
    HasRawPredictionCol
  35. final def getRegParam: Double

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    Definition Classes
    SVMBase
  36. final def getStepSize: Double

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    Definition Classes
    SVMBase
  37. final def getThreshold: Double

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    Definition Classes
    SVMBase
  38. def getThresholds: Array[Double]

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    Definition Classes
    HasThresholds
  39. final def hasDefault[T](param: Param[T]): Boolean

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

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    Definition Classes
    Params
  41. def hasParent: Boolean

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    Definition Classes
    Model
  42. def hashCode(): Int

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    Definition Classes
    AnyRef → Any
  43. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  44. final def isDefined(param: Param[_]): Boolean

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

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

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    Definition Classes
    Params
  47. def isTraceEnabled(): Boolean

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    Attributes
    protected
    Definition Classes
    Logging
  48. final val labelCol: Param[String]

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    Definition Classes
    HasLabelCol
  49. def log: Logger

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

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

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  56. def logName: String

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  61. def margin(features: Vector): Double

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  62. final val miniBatchFraction: DoubleParam

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    Param for number of iterations.

    Param for number of iterations.

    Definition Classes
    SVMBase
  63. val model: mllib.classification.SVMModel

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

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

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

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    Definition Classes
    AnyRef
  67. def numClasses: Int

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    Definition Classes
    SVMModel → ClassificationModel
  68. def numFeatures: Int

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    Definition Classes
    PredictionModel
    Annotations
    @Since( "1.6.0" )
  69. final val numIterations: IntParam

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    Param for number of iterations.

    Param for number of iterations.

    Definition Classes
    SVMBase
  70. lazy val params: Array[Param[_]]

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    Definition Classes
    Params
  71. var parent: Estimator[SVMModel]

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    Definition Classes
    Model
  72. def predict(features: Vector): Double

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    Attributes
    protected
    Definition Classes
    SVMModel → ClassificationModel → PredictionModel
  73. def predictProbability(features: Vector): Vector

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    Attributes
    protected
    Definition Classes
    ProbabilisticClassificationModel
  74. def predictRaw(features: Vector): Vector

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    Attributes
    protected
    Definition Classes
    SVMModel → ClassificationModel
  75. final val predictionCol: Param[String]

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    Definition Classes
    HasPredictionCol
  76. def probability2prediction(probability: Vector): Double

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    Attributes
    protected
    Definition Classes
    ProbabilisticClassificationModel
  77. final val probabilityCol: Param[String]

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    Definition Classes
    HasProbabilityCol
  78. def raw2prediction(rawPrediction: Vector): Double

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    Attributes
    protected
    Definition Classes
    ProbabilisticClassificationModel → ClassificationModel
  79. def raw2probability(rawPrediction: Vector): Vector

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    Attributes
    protected
    Definition Classes
    ProbabilisticClassificationModel
  80. def raw2probabilityInPlace(rawPrediction: Vector): Vector

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    Attributes
    protected
    Definition Classes
    SVMModel → ProbabilisticClassificationModel
  81. final val rawPredictionCol: Param[String]

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    Definition Classes
    HasRawPredictionCol
  82. final val regParam: DoubleParam

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    Param for number of iterations.

    Param for number of iterations.

    Definition Classes
    SVMBase
  83. final def set(paramPair: ParamPair[_]): SVMModel.this.type

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

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

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    Definition Classes
    Params
  86. final def setDefault(paramPairs: ParamPair[_]*): SVMModel.this.type

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

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    Attributes
    protected
    Definition Classes
    Params
  88. def setFeaturesCol(value: String): SVMModel

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    Definition Classes
    PredictionModel
  89. def setParent(parent: Estimator[SVMModel]): SVMModel

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    Definition Classes
    Model
  90. def setPredictionCol(value: String): SVMModel

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    Definition Classes
    PredictionModel
  91. def setProbabilityCol(value: String): SVMModel

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    Definition Classes
    ProbabilisticClassificationModel
  92. def setRawPredictionCol(value: String): SVMModel

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    Definition Classes
    ClassificationModel
  93. def setThreshold(value: Double): SVMModel.this.type

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  94. def setThresholds(value: Array[Double]): SVMModel

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    Definition Classes
    ProbabilisticClassificationModel
  95. final val stepSize: DoubleParam

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    Param for step size.

    Param for step size.

    Definition Classes
    SVMBase
  96. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  97. final val threshold: DoubleParam

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    Param for threshold.

    Param for threshold.

    Definition Classes
    SVMBase
  98. final val thresholds: DoubleArrayParam

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    Definition Classes
    HasThresholds
  99. def toString(): String

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    Definition Classes
    Identifiable → AnyRef → Any
  100. def transform(dataset: Dataset[_]): DataFrame

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    Definition Classes
    ProbabilisticClassificationModel → ClassificationModel → PredictionModel → Transformer
  101. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame

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    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  102. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame

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    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  103. def transformImpl(dataset: Dataset[_]): DataFrame

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    Attributes
    protected
    Definition Classes
    PredictionModel
  104. def transformSchema(schema: StructType): StructType

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    Definition Classes
    PredictionModel → PipelineStage
  105. def transformSchema(schema: StructType, logging: Boolean): StructType

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

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    Definition Classes
    SVMModel → Identifiable
  107. def validateAndTransformSchema(schema: StructType, fitting: Boolean, featuresDataType: DataType): StructType

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    Attributes
    protected
    Definition Classes
    ProbabilisticClassifierParams → ClassifierParams → PredictorParams
  108. final def wait(): Unit

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

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from SVMBase

Inherited from ProbabilisticClassificationModel[Vector, SVMModel]

Inherited from ProbabilisticClassifierParams

Inherited from HasThresholds

Inherited from HasProbabilityCol

Inherited from ClassificationModel[Vector, SVMModel]

Inherited from ClassifierParams

Inherited from HasRawPredictionCol

Inherited from PredictionModel[Vector, SVMModel]

Inherited from PredictorParams

Inherited from HasPredictionCol

Inherited from HasFeaturesCol

Inherited from HasLabelCol

Inherited from Model[SVMModel]

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

getParam

param

Ungrouped