BoostingRegressor

Value Members

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

   

   Definition Classes

   AnyRef → Any

2. final def ##(): Int

   

   Definition Classes

   AnyRef → Any

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

   

   Attributes

   protected

   Definition Classes

   Params

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

   

   Definition Classes

   AnyRef → Any

5. final def asInstanceOf[T0]: T0

   

   Definition Classes

   Any

6. val baseLearner: Param[EnsemblePredictorType]

   

   param for the estimator that will be used by the ensemble learner as a base learner

   param for the estimator that will be used by the ensemble learner as a base learner

   Definition Classes

   HasBaseLearner

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

   

   Definition Classes

   Params

8. def clone(): AnyRef

   

   Attributes

   protected[java.lang]

   Definition Classes

   AnyRef

   Annotations

   @throws( ... )

9. def copy(extra: ParamMap): BoostingRegressor

   

   Definition Classes

   BoostingRegressor → Predictor → Estimator → PipelineStage → Params

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

    

    Attributes

    protected

    Definition Classes

    Params

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

    

    Attributes

    protected

    Definition Classes

    Params

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

    

    Definition Classes

    AnyRef

13. def equals(arg0: Any): Boolean

    

    Definition Classes

    AnyRef → Any

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

    

    Definition Classes

    Params

15. def explainParams(): String

    

    Definition Classes

    Params

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

    

    Attributes

    protected

    Definition Classes

    Predictor

17. final def extractParamMap(): ParamMap

    

    Definition Classes

    Params

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

    

    Definition Classes

    Params

19. final val featuresCol: Param[String]

    

    Definition Classes

    HasFeaturesCol

20. def finalize(): Unit

    

    Attributes

    protected[java.lang]

    Definition Classes

    AnyRef

    Annotations

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

21. def fit(dataset: Dataset[_]): BoostingRegressionModel

    

    Definition Classes

    Predictor → Estimator

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

    

    Definition Classes

    Estimator

    Annotations

    @Since( "2.0.0" )

23. def fit(dataset: Dataset[_], paramMap: ParamMap): BoostingRegressionModel

    

    Definition Classes

    Estimator

    Annotations

    @Since( "2.0.0" )

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

    

    Definition Classes

    Estimator

    Annotations

    @Since( "2.0.0" ) @varargs()

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

    

    Definition Classes

    Params

26. def getBaseLearner: EnsemblePredictorType

    
    Definition Classes

    HasBaseLearner

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

    

    Definition Classes

    AnyRef → Any

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

    

    Definition Classes

    Params

29. final def getFeaturesCol: String

    

    Definition Classes

    HasFeaturesCol

30. final def getLabelCol: String

    

    Definition Classes

    HasLabelCol

31. def getLearningRate: Double

    
    Definition Classes

    HasLearningRate

32. def getLoss: String

    
    Definition Classes

    BoostingRegressorParams

33. final def getMaxIter: Int

    

    Definition Classes

    HasMaxIter

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

    

    Definition Classes

    Params

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

    

    Definition Classes

    Params

36. final def getPredictionCol: String

    

    Definition Classes

    HasPredictionCol

37. final def getSeed: Long

    

    Definition Classes

    HasSeed

38. final def getWeightCol: String

    

    Definition Classes

    HasWeightCol

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

    

    Definition Classes

    Params

40. def hasParam(paramName: String): Boolean

    

    Definition Classes

    Params

41. def hashCode(): Int

    

    Definition Classes

    AnyRef → Any

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

    

    Attributes

    protected

    Definition Classes

    Logging

43. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

    

    Attributes

    protected

    Definition Classes

    Logging

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

    

    Definition Classes

    Params

45. final def isInstanceOf[T0]: Boolean

    

    Definition Classes

    Any

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

    

    Definition Classes

    Params

47. def isTraceEnabled(): Boolean

    

    Attributes

    protected

    Definition Classes

    Logging

48. final val labelCol: Param[String]

    

    Definition Classes

    HasLabelCol

49. val learningRate: Param[Double]

    

    param for the learning rate of the algorithm

    param for the learning rate of the algorithm

    Definition Classes

    HasLearningRate

50. def log: Logger

    

    Attributes

    protected

    Definition Classes

    Logging

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

    

    Attributes

    protected

    Definition Classes

    Logging

52. def logDebug(msg: ⇒ String): Unit

    

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    protected

    Definition Classes

    Logging

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

    

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    protected

    Definition Classes

    Logging

54. def logError(msg: ⇒ String): Unit

    

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    protected

    Definition Classes

    Logging

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

    

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    protected

    Definition Classes

    Logging

56. def logInfo(msg: ⇒ String): Unit

    

    Attributes

    protected

    Definition Classes

    Logging

57. def logName: String

    

    Attributes

    protected

    Definition Classes

    Logging

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

    

    Attributes

    protected

    Definition Classes

    Logging

59. def logTrace(msg: ⇒ String): Unit

    

    Attributes

    protected

    Definition Classes

    Logging

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

    

    Attributes

    protected

    Definition Classes

    Logging

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

    

    Attributes

    protected

    Definition Classes

    Logging

62. val loss: Param[String]

    

    Loss function which Boosting tries to minimize.

    Loss function which Boosting tries to minimize. (case-insensitive) Supported: "exponential" (default = exponential)

    Definition Classes

    BoostingRegressorParams

63. final val maxIter: IntParam

    

    Definition Classes

    HasMaxIter

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

    

    Definition Classes

    AnyRef

65. final def notify(): Unit

    

    Definition Classes

    AnyRef

66. final def notifyAll(): Unit

    

    Definition Classes

    AnyRef

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

    

    Definition Classes

    Params

68. final val predictionCol: Param[String]

    

    Definition Classes

    HasPredictionCol

69. def save(path: String): Unit

    

    Definition Classes

    MLWritable

    Annotations

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

70. final val seed: LongParam

    

    Definition Classes

    HasSeed

71. final def set(paramPair: ParamPair[_]): BoostingRegressor.this.type

    

    Attributes

    protected

    Definition Classes

    Params

72. final def set(param: String, value: Any): BoostingRegressor.this.type

    

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    protected

    Definition Classes

    Params

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

    

    Definition Classes

    Params

74. def setBaseLearner(value: Predictor[_, _, _]): BoostingRegressor.this.type

    

75. final def setDefault(paramPairs: ParamPair[_]*): BoostingRegressor.this.type

    

    Attributes

    protected

    Definition Classes

    Params

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

    

    Attributes

    protected

    Definition Classes

    Params

77. def setFeaturesCol(value: String): BoostingRegressor

    

    Definition Classes

    Predictor

78. def setLabelCol(value: String): BoostingRegressor

    

    Definition Classes

    Predictor

79. def setLearningRate(value: Double): BoostingRegressor.this.type

    

80. def setLoss(value: String): BoostingRegressor.this.type

    

81. def setMaxIter(value: Int): BoostingRegressor.this.type

    

82. def setPredictionCol(value: String): BoostingRegressor

    

    Definition Classes

    Predictor

83. def setWeightCol(value: String): BoostingRegressor.this.type

    

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

    

    Definition Classes

    AnyRef

85. def toString(): String

    

    Definition Classes

    Identifiable → AnyRef → Any

86. def train(dataset: Dataset[_]): BoostingRegressionModel

    

    Attributes

    protected

    Definition Classes

    BoostingRegressor → Predictor

87. def transformSchema(schema: StructType): StructType

    

    Definition Classes

    Predictor → PipelineStage

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

    

    Attributes

    protected

    Definition Classes

    PipelineStage

    Annotations

    @DeveloperApi()

89. val uid: String

    

    Definition Classes

    BoostingRegressor → Identifiable

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

    

    Attributes

    protected

    Definition Classes

    PredictorParams

91. final def wait(): Unit

    

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

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

    

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

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

    

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

94. final val weightCol: Param[String]

    

    Definition Classes

    HasWeightCol

95. def write: MLWriter

    

    Definition Classes

    BoostingRegressor → MLWritable