BaggingRegressionModel

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[_]): BaggingRegressionModel.this.type

   

   Definition Classes

   Params

8. def clone(): AnyRef

   

   Attributes

   protected[java.lang]

   Definition Classes

   AnyRef

   Annotations

   @throws( ... )

9. def copy(extra: ParamMap): BaggingRegressionModel

   

   Definition Classes

   BaggingRegressionModel → Model → Transformer → 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. final def extractParamMap(): ParamMap

    

    Definition Classes

    Params

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

    

    Definition Classes

    Params

18. def extractSubBag(bagColName: String, index: Int, featuresColName: String, subspace: SubSpace)(df: DataFrame): DataFrame

    

    Definition Classes

    HasSubBag

19. final val featuresCol: Param[String]

    

    Definition Classes

    HasFeaturesCol

20. def featuresDataType: DataType

    

    Attributes

    protected

    Definition Classes

    PredictionModel

21. def finalize(): Unit

    

    Attributes

    protected[java.lang]

    Definition Classes

    AnyRef

    Annotations

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

22. def fitBaseLearner(baseLearner: EnsemblePredictorType, labelColName: String, featuresColName: String, predictionColName: String, weightColName: Option[String])(df: DataFrame): EnsemblePredictionModelType

    

    Definition Classes

    HasBaseLearner

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

    

    Definition Classes

    Params

24. def getBaseLearner: EnsemblePredictorType

    
    Definition Classes

    HasBaseLearner

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. def getNumBaseLearners: Int

    
    Definition Classes

    HasNumBaseLearners

30. def getNumFeatures(dataset: DataFrame, featuresCol: String): Int

    

    Definition Classes

    HasSubBag

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

    

    Definition Classes

    Params

32. def getParallelism: Int

    

    Definition Classes

    HasParallelism

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

    

    Definition Classes

    Params

34. final def getPredictionCol: String

    

    Definition Classes

    HasPredictionCol

35. def getReplacement: Boolean

    
    Definition Classes

    HasSubBag

36. def getSampleRatio: Double

    
    Definition Classes

    HasSubBag

37. final def getSeed: Long

    

    Definition Classes

    HasSeed

38. def getSubspaceRatio: Double

    
    Definition Classes

    HasSubBag

39. final def getWeightCol: String

    

    Definition Classes

    HasWeightCol

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

    

    Definition Classes

    Params

41. def hasParam(paramName: String): Boolean

    

    Definition Classes

    Params

42. def hasParent: Boolean

    

    Definition Classes

    Model

43. def hashCode(): Int

    

    Definition Classes

    AnyRef → Any

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

    

    Attributes

    protected

    Definition Classes

    Logging

45. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

    

    Attributes

    protected

    Definition Classes

    Logging

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

    

    Definition Classes

    Params

47. final def isInstanceOf[T0]: Boolean

    

    Definition Classes

    Any

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

    

    Definition Classes

    Params

49. def isTraceEnabled(): Boolean

    

    Attributes

    protected

    Definition Classes

    Logging

50. final val labelCol: Param[String]

    

    Definition Classes

    HasLabelCol

51. def log: Logger

    

    Attributes

    protected

    Definition Classes

    Logging

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

    

    Attributes

    protected

    Definition Classes

    Logging

53. def logDebug(msg: ⇒ String): Unit

    

    Attributes

    protected

    Definition Classes

    Logging

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

    

    Attributes

    protected

    Definition Classes

    Logging

55. def logError(msg: ⇒ String): Unit

    

    Attributes

    protected

    Definition Classes

    Logging

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

    

    Attributes

    protected

    Definition Classes

    Logging

57. def logInfo(msg: ⇒ String): Unit

    

    Attributes

    protected

    Definition Classes

    Logging

58. def logName: String

    

    Attributes

    protected

    Definition Classes

    Logging

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

    

    Attributes

    protected

    Definition Classes

    Logging

60. def logTrace(msg: ⇒ String): Unit

    

    Attributes

    protected

    Definition Classes

    Logging

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

    

    Attributes

    protected

    Definition Classes

    Logging

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

    

    Attributes

    protected

    Definition Classes

    Logging

63. def mkSubspace(sampleRatio: Double, numFeatures: Int, seed: Long): SubSpace

    

    Definition Classes

    HasSubBag

64. val models: Array[EnsemblePredictionModelType]

    

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

    

    Definition Classes

    AnyRef

66. final def notify(): Unit

    

    Definition Classes

    AnyRef

67. final def notifyAll(): Unit

    

    Definition Classes

    AnyRef

68. val numBaseLearners: Param[Int]

    

    param for the number of base learners of the algorithm

    param for the number of base learners of the algorithm

    Definition Classes

    HasNumBaseLearners

69. val numBaseModels: Int

    

70. def numFeatures: Int

    

    Definition Classes

    PredictionModel

    Annotations

    @Since( "1.6.0" )

71. val parallelism: IntParam

    

    Definition Classes

    HasParallelism

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

    

    Definition Classes

    Params

73. var parent: Estimator[BaggingRegressionModel]

    

    Definition Classes

    Model

74. def predict(features: Vector): Double

    

    Definition Classes

    BaggingRegressionModel → PredictionModel

75. final val predictionCol: Param[String]

    

    Definition Classes

    HasPredictionCol

76. val replacement: Param[Boolean]

    

    param for whether samples are drawn with replacement

    param for whether samples are drawn with replacement

    Definition Classes

    HasSubBag

77. val sampleRatio: Param[Double]

    

    param for ratio of rows sampled out of the dataset

    param for ratio of rows sampled out of the dataset

    Definition Classes

    HasSubBag

78. def save(path: String): Unit

    

    Definition Classes

    MLWritable

    Annotations

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

79. final val seed: LongParam

    

    Definition Classes

    HasSeed

80. final def set(paramPair: ParamPair[_]): BaggingRegressionModel.this.type

    

    Attributes

    protected

    Definition Classes

    Params

81. final def set(param: String, value: Any): BaggingRegressionModel.this.type

    

    Attributes

    protected

    Definition Classes

    Params

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

    

    Definition Classes

    Params

83. final def setDefault(paramPairs: ParamPair[_]*): BaggingRegressionModel.this.type

    

    Attributes

    protected

    Definition Classes

    Params

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

    

    Attributes

    protected

    Definition Classes

    Params

85. def setFeaturesCol(value: String): BaggingRegressionModel

    

    Definition Classes

    PredictionModel

86. def setParent(parent: Estimator[BaggingRegressionModel]): BaggingRegressionModel

    

    Definition Classes

    Model

87. def setPredictionCol(value: String): BaggingRegressionModel

    

    Definition Classes

    PredictionModel

88. def slicer(subspace: SubSpace): (Vector) ⇒ Vector

    

    Definition Classes

    HasSubBag

89. val subspaceRatio: Param[Double]

    

    param for ratio of rows sampled out of the dataset

    param for ratio of rows sampled out of the dataset

    Definition Classes

    HasSubBag

90. val subspaces: Array[SubSpace]

    

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

    

    Definition Classes

    AnyRef

92. def toString(): String

    

    Definition Classes

    Identifiable → AnyRef → Any

93. def transform(dataset: Dataset[_]): DataFrame

    

    Definition Classes

    PredictionModel → Transformer

94. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame

    

    Definition Classes

    Transformer

    Annotations

    @Since( "2.0.0" )

95. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame

    

    Definition Classes

    Transformer

    Annotations

    @Since( "2.0.0" ) @varargs()

96. def transformImpl(dataset: Dataset[_]): DataFrame

    

    Attributes

    protected

    Definition Classes

    PredictionModel

97. def transformSchema(schema: StructType): StructType

    

    Definition Classes

    PredictionModel → PipelineStage

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

    

    Attributes

    protected

    Definition Classes

    PipelineStage

    Annotations

    @DeveloperApi()

99. val uid: String

    

    Definition Classes

    BaggingRegressionModel → Identifiable

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

     

     Attributes

     protected

     Definition Classes

     PredictorParams

101. final def wait(): Unit

     

     Definition Classes

     AnyRef

     Annotations

     @throws( ... )

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

     

     Definition Classes

     AnyRef

     Annotations

     @throws( ... )

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

     

     Definition Classes

     AnyRef

     Annotations

     @throws( ... )

104. final val weightCol: Param[String]

     

     Definition Classes

     HasWeightCol

105. def withBag(withReplacement: Boolean, sampleRatio: Double, numberSamples: Int, seed: Long, bagColName: String)(df: DataFrame): DataFrame

     

     Definition Classes

     HasSubBag

106. def write: MLWriter

     

     Definition Classes

     BaggingRegressionModel → MLWritable