TuneHyperparameters

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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   Params

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

   

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5. def additionalPythonMethods(): String

   

   Definition Classes

   Wrappable

6. final def asInstanceOf[T0]: T0

   

   Definition Classes

   Any

7. final def clear(param: Param[_]): TuneHyperparameters.this.type

   

   Definition Classes

   Params

8. def clone(): AnyRef

   

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   protected[java.lang]

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   AnyRef

   Annotations

   @throws( ... )

9. def copy(extra: ParamMap): Estimator[TuneHyperparametersModel]

   

   Definition Classes

   TuneHyperparameters → Estimator → PipelineStage → Params

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

    

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    Definition Classes

    Params

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

    

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    Params

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

    

    Definition Classes

    AnyRef

13. def equals(arg0: Any): Boolean

    

    Definition Classes

    AnyRef → Any

14. val evaluationMetric: Param[String]

    

    Definition Classes

    HasEvaluationMetric

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

    

    Definition Classes

    Params

16. def explainParams(): String

    

    Definition Classes

    Params

17. final def extractParamMap(): ParamMap

    

    Definition Classes

    Params

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

    

    Definition Classes

    Params

19. def finalize(): Unit

    

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    protected[java.lang]

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    AnyRef

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

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

    

    Tunes model hyperparameters for given number of runs and returns the best model found based on evaluation metric.

    Tunes model hyperparameters for given number of runs and returns the best model found based on evaluation metric.

    dataset

    The input dataset to train.

    returns

    The trained classification model.

    Definition Classes

    TuneHyperparameters → Estimator

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

    

    Definition Classes

    Estimator

    Annotations

    @Since( "2.0.0" )

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

    

    Definition Classes

    Estimator

    Annotations

    @Since( "2.0.0" )

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

    

    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. def getEvaluationMetric: String

    
    Definition Classes

    HasEvaluationMetric

28. def getModels: Array[Estimator[_]]

    

29. def getNumFolds: Int

    

30. def getNumRuns: Int

    

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

    

    Definition Classes

    Params

32. def getParallelism: Int

    

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

    

    Definition Classes

    Params

34. def getParamSpace: ParamSpace

    

35. def getSeed: Long

    

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

    

    Definition Classes

    Params

37. def hasParam(paramName: String): Boolean

    

    Definition Classes

    Params

38. def hashCode(): Int

    

    Definition Classes

    AnyRef → Any

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

    

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    Logging

40. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

    

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    Logging

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

    

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42. final def isInstanceOf[T0]: Boolean

    

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    Any

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

    

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    Params

44. def isTraceEnabled(): Boolean

    

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    Logging

45. def log: Logger

    

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    Logging

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

    

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    Logging

47. def logDebug(msg: ⇒ String): Unit

    

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    Logging

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

    

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    Logging

49. def logError(msg: ⇒ String): Unit

    

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    Logging

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

    

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    Logging

51. def logInfo(msg: ⇒ String): Unit

    

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    Logging

52. def logName: String

    

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    Logging

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

    

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    Logging

54. def logTrace(msg: ⇒ String): Unit

    

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    Logging

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

    

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    Logging

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

    

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    Logging

57. val models: EstimatorArrayParam

    

    Estimators to run

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

    

    Definition Classes

    AnyRef

59. final def notify(): Unit

    

    Definition Classes

    AnyRef

60. final def notifyAll(): Unit

    

    Definition Classes

    AnyRef

61. val numFolds: IntParam

    

62. val numRuns: IntParam

    

63. val parallelism: IntParam

    

64. val paramSpace: ParamSpaceParam

    

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

    

    Definition Classes

    Params

66. def save(path: String): Unit

    

    Definition Classes

    MLWritable

    Annotations

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

67. val seed: LongParam

    

68. final def set(paramPair: ParamPair[_]): TuneHyperparameters.this.type

    

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69. final def set(param: String, value: Any): TuneHyperparameters.this.type

    

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    Params

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

    

    Definition Classes

    Params

71. final def setDefault(paramPairs: ParamPair[_]*): TuneHyperparameters.this.type

    

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

    

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    Definition Classes

    Params

73. def setEvaluationMetric(value: String): TuneHyperparameters.this.type

    
    Definition Classes

    HasEvaluationMetric

74. def setModels(value: Array[Estimator[_]]): TuneHyperparameters.this.type

    

75. def setNumFolds(value: Int): TuneHyperparameters.this.type

    

76. def setNumRuns(value: Int): TuneHyperparameters.this.type

    

77. def setParallelism(value: Int): TuneHyperparameters.this.type

    

78. def setParamSpace(value: ParamSpace): TuneHyperparameters.this.type

    

79. def setSeed(value: Long): TuneHyperparameters.this.type

    

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

    

    Definition Classes

    AnyRef

81. def toString(): String

    

    Definition Classes

    Identifiable → AnyRef → Any

82. def transformSchema(schema: StructType): StructType

    

    Definition Classes

    TuneHyperparameters → PipelineStage

    Annotations

    @DeveloperApi()

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

    

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    Definition Classes

    PipelineStage

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    @DeveloperApi()

84. val uid: String

    

    Definition Classes

    TuneHyperparameters → Identifiable

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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    @throws( ... )

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

    

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    AnyRef

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    @throws( ... )

88. def write: MLWriter

    

    Definition Classes

    ComplexParamsWritable → MLWritable