UnsupervisedPretrainingSolver

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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5. final def asInstanceOf[T0]: T0

   

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   Any

6. final def clear(param: Param[_]): UnsupervisedPretrainingSolver.this.type

   

   Definition Classes

   Params

7. def clone(): AnyRef

   

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   protected[java.lang]

   Definition Classes

   AnyRef

   Annotations

   @throws( ... )

8. def copy(extra: ParamMap): UnsupervisedPretrainingSolver

   

   Definition Classes

   UnsupervisedPretrainingSolver → Predictor → Estimator → PipelineStage → Params

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

   

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

    

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    Params

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

    

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    AnyRef

12. def equals(arg0: Any): Boolean

    

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    AnyRef → Any

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

    

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    Params

14. def explainParams(): String

    

    Definition Classes

    Params

15. def extractLabeledPoints(dataset: Dataset[_]): RDD[LabeledPoint]

    

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    Definition Classes

    Predictor

16. final def extractParamMap(): ParamMap

    

    Definition Classes

    Params

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

    

    Definition Classes

    Params

18. final val featuresCol: Param[String]

    

    Definition Classes

    HasFeaturesCol

19. def finalize(): Unit

    

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    protected[java.lang]

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    AnyRef

    Annotations

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

20. def fit(dataset: Dataset[_]): UnsupervisedPretrainingSolverModel

    

    Definition Classes

    Predictor → Estimator

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

    

    Definition Classes

    Estimator

    Annotations

    @Since( "2.0.0" )

22. def fit(dataset: Dataset[_], paramMap: ParamMap): UnsupervisedPretrainingSolverModel

    

    Definition Classes

    Estimator

    Annotations

    @Since( "2.0.0" )

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

    

    Definition Classes

    Estimator

    Annotations

    @Since( "2.0.0" ) @varargs()

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

    

    Definition Classes

    Params

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

    

    Definition Classes

    AnyRef → Any

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

    

    Definition Classes

    Params

27. final def getFeaturesCol: String

    

    Definition Classes

    HasFeaturesCol

28. final def getLabelCol: String

    

    Definition Classes

    HasLabelCol

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

    

    Definition Classes

    Params

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

    

    Definition Classes

    Params

31. final def getPredictionCol: String

    

    Definition Classes

    HasPredictionCol

32. final def getWeightCol: String

    
    Definition Classes

    HasWeightCol

33. def gradient(form: Graph, model: Model, instance: Instance): (Model, Double)

    

    Calculate the gradient of Model parameter with given training instance.

    Calculate the gradient of Model parameter with given training instance.

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    protected

    Definition Classes

    Solver

34. val graph: Graph

    

    Definition Classes

    Solver

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

    

    Definition Classes

    Params

36. def hasParam(paramName: String): Boolean

    

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    Params

37. def hashCode(): Int

    

    Definition Classes

    AnyRef → Any

38. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

    

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    Definition Classes

    Logging

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

    

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    Params

40. final def isInstanceOf[T0]: Boolean

    

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    Any

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

    

    Definition Classes

    Params

42. def isTraceEnabled(): Boolean

    

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    protected

    Definition Classes

    Logging

43. final val labelCol: Param[String]

    

    Definition Classes

    HasLabelCol

44. var learningRate: Double

    

    Definition Classes

    Solver

45. val learningRateDecay: Double

    

    Definition Classes

    Solver

46. def log: Logger

    

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    Logging

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

    

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    Logging

48. def logDebug(msg: ⇒ String): Unit

    

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    Logging

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

    

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    Logging

50. def logError(msg: ⇒ String): Unit

    

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    Logging

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

    

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    Logging

52. def logInfo(msg: ⇒ String): Unit

    

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    Logging

53. def logName: String

    

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    Logging

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

    

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    Logging

55. def logTrace(msg: ⇒ String): Unit

    

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    Logging

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

    

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    Logging

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

    

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    Definition Classes

    Logging

58. var miniBatchFraction: Double

    

    Definition Classes

    Solver

59. val model: Model

    

    Definition Classes

    Solver

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

    

    Definition Classes

    AnyRef

61. val network: Network

    

    Definition Classes

    Solver

62. final def notify(): Unit

    

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    AnyRef

63. final def notifyAll(): Unit

    

    Definition Classes

    AnyRef

64. var numIterations: Int

    

    Definition Classes

    Solver

65. val objective: Objective

    

    Definition Classes

    Solver

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

    

    Definition Classes

    Params

67. final val predictionCol: Param[String]

    

    Definition Classes

    HasPredictionCol

68. def pretrainInternal(dataset: Dataset[_], model: Model): Model

    

    Definition Classes

    Pretrainer

69. final def set(paramPair: ParamPair[_]): UnsupervisedPretrainingSolver.this.type

    

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    Params

70. final def set(param: String, value: Any): UnsupervisedPretrainingSolver.this.type

    

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

    

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    Params

72. final def setDefault(paramPairs: ParamPair[_]*): UnsupervisedPretrainingSolver.this.type

    

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

    

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    Definition Classes

    Params

74. def setFeaturesCol(value: String): UnsupervisedPretrainingSolver

    

    Definition Classes

    Predictor

75. def setLabelCol(value: String): UnsupervisedPretrainingSolver

    

    Definition Classes

    Predictor

76. def setPredictionCol(value: String): UnsupervisedPretrainingSolver

    

    Definition Classes

    Predictor

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

    

    Definition Classes

    AnyRef

78. def toString(): String

    

    Definition Classes

    Identifiable → AnyRef → Any

79. def train(dataset: Dataset[_]): UnsupervisedPretrainingSolverModel

    

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    Definition Classes

    UnsupervisedPretrainingSolver → Predictor

80. def trainInternal(dataset: Dataset[_], model: Model): Model

    

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    Definition Classes

    Solver

81. def transformSchema(schema: StructType): StructType

    

    Definition Classes

    Predictor → PipelineStage

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

    

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    protected

    Definition Classes

    PipelineStage

    Annotations

    @DeveloperApi()

83. val uid: String

    

    Definition Classes

    UnsupervisedPretrainingSolver → Identifiable

84. def validateAndTransformSchema(schema: StructType, fitting: Boolean, featuresDataType: DataType): StructType

    

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    Definition Classes

    PredictorParams

85. final def wait(): Unit

    

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    AnyRef

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    @throws( ... )

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

    

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    AnyRef

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    @throws( ... )

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

    

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    AnyRef

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    @throws( ... )

88. final val weightCol: Param[String]

    

    Param for weight column name.

    Param for weight column name. If this is not set or empty, we treat all instance weights as 1.0..

    Definition Classes

    HasWeightCol