BoostingClassificationModel

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

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   Definition Classes

   Params

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

   

   Definition Classes

   AnyRef → Any

5. final def asInstanceOf[T0]: T0

   

   Definition Classes

   Any

6. def avgLoss(lossColName: String, boostProbaColName: String)(df: DataFrame): Double

   

   Definition Classes

   BoostingParams

7. 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

8. def beta(avgl: Double, numClasses: Int = 2): Double

   

   Definition Classes

   BoostingParams

9. final def clear(param: Param[_]): BoostingClassificationModel.this.type

   

   Definition Classes

   Params

10. def clone(): AnyRef

    

    Attributes

    protected[java.lang]

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

11. def copy(extra: ParamMap): BoostingClassificationModel

    

    Definition Classes

    BoostingClassificationModel → Model → Transformer → PipelineStage → Params

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

    

    Attributes

    protected

    Definition Classes

    Params

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

    

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    protected

    Definition Classes

    Params

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

    

    Definition Classes

    AnyRef

15. def equals(arg0: Any): Boolean

    

    Definition Classes

    AnyRef → Any

16. def evaluateOnValidation(numClasses: Int, weights: Array[Double], boosters: Array[EnsemblePredictionModelType], labelColName: String, featuresColName: String, loss: (Double) ⇒ Double)(df: DataFrame): Double

    

    Definition Classes

    BoostingParams

17. def evaluateOnValidation(weights: Array[Double], boosters: Array[EnsemblePredictionModelType], labelColName: String, featuresColName: String, loss: (Double) ⇒ Double)(df: DataFrame): Double

    

    Definition Classes

    BoostingParams

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

    

    Definition Classes

    Params

19. def explainParams(): String

    

    Definition Classes

    Params

20. def extractBoostedBag(poissonProbaColName: String, seed: Long)(df: DataFrame): DataFrame

    

    Definition Classes

    BoostingParams

21. final def extractParamMap(): ParamMap

    

    Definition Classes

    Params

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

    

    Definition Classes

    Params

23. final val featuresCol: Param[String]

    

    Definition Classes

    HasFeaturesCol

24. def featuresDataType: DataType

    

    Attributes

    protected

    Definition Classes

    PredictionModel

25. def finalize(): Unit

    

    Attributes

    protected[java.lang]

    Definition Classes

    AnyRef

    Annotations

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

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

    

    Definition Classes

    HasBaseLearner

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

    

    Definition Classes

    Params

28. def getBaseLearner: EnsemblePredictorType

    
    Definition Classes

    HasBaseLearner

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

    

    Definition Classes

    AnyRef → Any

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

    

    Definition Classes

    Params

31. final def getFeaturesCol: String

    

    Definition Classes

    HasFeaturesCol

32. final def getLabelCol: String

    

    Definition Classes

    HasLabelCol

33. def getLoss: String

    
    Definition Classes

    BoostingClassifierParams

34. def getNumBaseLearners: Int

    
    Definition Classes

    HasNumBaseLearners

35. def getNumRound: Int

    
    Definition Classes

    HasNumRound

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

    

    Definition Classes

    Params

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

    

    Definition Classes

    Params

38. final def getPredictionCol: String

    

    Definition Classes

    HasPredictionCol

39. final def getRawPredictionCol: String

    

    Definition Classes

    HasRawPredictionCol

40. final def getSeed: Long

    

    Definition Classes

    HasSeed

41. final def getTol: Double

    

    Definition Classes

    HasTol

42. final def getValidationIndicatorCol: String

    

    Definition Classes

    HasValidationIndicatorCol

43. final def getWeightCol: String

    

    Definition Classes

    HasWeightCol

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

    

    Definition Classes

    Params

45. def hasParam(paramName: String): Boolean

    

    Definition Classes

    Params

46. def hasParent: Boolean

    

    Definition Classes

    Model

47. def hashCode(): Int

    

    Definition Classes

    AnyRef → Any

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

    

    Attributes

    protected

    Definition Classes

    Logging

49. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

    

    Attributes

    protected

    Definition Classes

    Logging

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

    

    Definition Classes

    Params

51. final def isInstanceOf[T0]: Boolean

    

    Definition Classes

    Any

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

    

    Definition Classes

    Params

53. def isTraceEnabled(): Boolean

    

    Attributes

    protected

    Definition Classes

    Logging

54. final val labelCol: Param[String]

    

    Definition Classes

    HasLabelCol

55. def log: Logger

    

    Attributes

    protected

    Definition Classes

    Logging

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

    

    Attributes

    protected

    Definition Classes

    Logging

57. def logDebug(msg: ⇒ String): Unit

    

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    Definition Classes

    Logging

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

    

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    Definition Classes

    Logging

59. def logError(msg: ⇒ String): Unit

    

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    protected

    Definition Classes

    Logging

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

    

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    Definition Classes

    Logging

61. def logInfo(msg: ⇒ String): Unit

    

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    Definition Classes

    Logging

62. def logName: String

    

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    protected

    Definition Classes

    Logging

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

    

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    Definition Classes

    Logging

64. def logTrace(msg: ⇒ String): Unit

    

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    protected

    Definition Classes

    Logging

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

    

    Attributes

    protected

    Definition Classes

    Logging

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

    

    Attributes

    protected

    Definition Classes

    Logging

67. 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

    BoostingClassifierParams

68. val models: Array[EnsemblePredictionModelType]

    

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

    

    Definition Classes

    AnyRef

70. final def notify(): Unit

    

    Definition Classes

    AnyRef

71. final def notifyAll(): Unit

    

    Definition Classes

    AnyRef

72. 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

73. val numBaseModels: Int

    

74. val numClasses: Int

    

    Definition Classes

    BoostingClassificationModel → ClassificationModel

75. def numFeatures: Int

    

    Definition Classes

    PredictionModel

    Annotations

    @Since( "1.6.0" )

76. val numRound: Param[Int]

    

    param for the number of round waiting for next decrease in validation set

    param for the number of round waiting for next decrease in validation set

    Definition Classes

    HasNumRound

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

    

    Definition Classes

    Params

78. var parent: Estimator[BoostingClassificationModel]

    

    Definition Classes

    Model

79. def predict(features: Vector): Double

    

    Definition Classes

    ClassificationModel → PredictionModel

80. def predictRaw(features: Vector): Vector

    

    Attributes

    protected

    Definition Classes

    BoostingClassificationModel → ClassificationModel

81. final val predictionCol: Param[String]

    

    Definition Classes

    HasPredictionCol

82. def probabilize(boostWeightColName: String, boostProbaColName: String, poissonProbaColName: String)(df: DataFrame): DataFrame

    

    Definition Classes

    BoostingParams

83. def raw2prediction(rawPrediction: Vector): Double

    

    Attributes

    protected

    Definition Classes

    ClassificationModel

84. final val rawPredictionCol: Param[String]

    

    Definition Classes

    HasRawPredictionCol

85. def save(path: String): Unit

    

    Definition Classes

    MLWritable

    Annotations

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

86. final val seed: LongParam

    

    Definition Classes

    HasSeed

87. final def set(paramPair: ParamPair[_]): BoostingClassificationModel.this.type

    

    Attributes

    protected

    Definition Classes

    Params

88. final def set(param: String, value: Any): BoostingClassificationModel.this.type

    

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    protected

    Definition Classes

    Params

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

    

    Definition Classes

    Params

90. final def setDefault(paramPairs: ParamPair[_]*): BoostingClassificationModel.this.type

    

    Attributes

    protected

    Definition Classes

    Params

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

    

    Attributes

    protected

    Definition Classes

    Params

92. def setFeaturesCol(value: String): BoostingClassificationModel

    

    Definition Classes

    PredictionModel

93. def setParent(parent: Estimator[BoostingClassificationModel]): BoostingClassificationModel

    

    Definition Classes

    Model

94. def setPredictionCol(value: String): BoostingClassificationModel

    

    Definition Classes

    PredictionModel

95. def setRawPredictionCol(value: String): BoostingClassificationModel

    

    Definition Classes

    ClassificationModel

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

    

    Definition Classes

    AnyRef

97. def terminate(avgl: Double, withValidation: Boolean, error: Double, verror: Double, tol: Double, numRound: Int, numTry: Int, iter: Int, instrumentation: Instrumentation, numClasses: Double = 2.0): (Int, Double, Int)

    

    Definition Classes

    BoostingParams

98. def terminateVal(withValidation: Boolean, error: Double, verror: Double, tol: Double, numRound: Int, numTry: Int, iter: Int, instrumentation: Instrumentation): (Int, Double, Int)

    

    Definition Classes

    BoostingParams

99. def toString(): String

    

    Definition Classes

    Identifiable → AnyRef → Any

100. final val tol: DoubleParam

     

     Definition Classes

     HasTol

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

     

     Definition Classes

     ClassificationModel → PredictionModel → Transformer

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

     

     Definition Classes

     Transformer

     Annotations

     @Since( "2.0.0" )

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

     

     Definition Classes

     Transformer

     Annotations

     @Since( "2.0.0" ) @varargs()

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

     

     Attributes

     protected

     Definition Classes

     PredictionModel

105. def transformSchema(schema: StructType): StructType

     

     Definition Classes

     PredictionModel → PipelineStage

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

     

     Attributes

     protected

     Definition Classes

     PipelineStage

     Annotations

     @DeveloperApi()

107. val uid: String

     

     Definition Classes

     BoostingClassificationModel → Identifiable

108. def updateWeights(boostWeightColName: String, lossColName: String, beta: Double, updatedBoostWeightColName: String)(df: DataFrame): DataFrame

     

     Definition Classes

     BoostingParams

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

     

     Attributes

     protected

     Definition Classes

     ClassifierParams → PredictorParams

110. final val validationIndicatorCol: Param[String]

     

     Definition Classes

     HasValidationIndicatorCol

111. final def wait(): Unit

     

     Definition Classes

     AnyRef

     Annotations

     @throws( ... )

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

     

     Definition Classes

     AnyRef

     Annotations

     @throws( ... )

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

     

     Definition Classes

     AnyRef

     Annotations

     @throws( ... )

114. def weight(beta: Double): Double

     

     Definition Classes

     BoostingParams

115. final val weightCol: Param[String]

     

     Definition Classes

     HasWeightCol

116. val weights: Array[Double]

     

117. def write: MLWriter

     

     Definition Classes

     BoostingClassificationModel → MLWritable