Class/Object

org.apache.spark.ml.regression

BoostingRegressor

Related Docs: object BoostingRegressor | package regression

Permalink

class BoostingRegressor extends Predictor[Vector, BoostingRegressor, BoostingRegressionModel] with BoostingRegressorParams with MLWritable

Linear Supertypes
MLWritable, BoostingRegressorParams, BoostingParams, HasNumRound, HasTol, HasValidationIndicatorCol, HasBaseLearner, HasSeed, HasWeightCol, HasNumBaseLearners, Predictor[Vector, BoostingRegressor, BoostingRegressionModel], PredictorParams, HasPredictionCol, HasFeaturesCol, HasLabelCol, Estimator[BoostingRegressionModel], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. BoostingRegressor
  2. MLWritable
  3. BoostingRegressorParams
  4. BoostingParams
  5. HasNumRound
  6. HasTol
  7. HasValidationIndicatorCol
  8. HasBaseLearner
  9. HasSeed
  10. HasWeightCol
  11. HasNumBaseLearners
  12. Predictor
  13. PredictorParams
  14. HasPredictionCol
  15. HasFeaturesCol
  16. HasLabelCol
  17. Estimator
  18. PipelineStage
  19. Logging
  20. Params
  21. Serializable
  22. Serializable
  23. Identifiable
  24. AnyRef
  25. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Instance Constructors

  1. new BoostingRegressor()

    Permalink

  2. new BoostingRegressor(uid: String)

    Permalink

Value Members

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

    Permalink
    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

    Permalink
    Definition Classes
    AnyRef → Any

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

    Permalink
    Attributes
    protected
    Definition Classes
    Params

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

    Permalink
    Definition Classes
    AnyRef → Any

  5. final def asInstanceOf[T0]: T0

    Permalink
    Definition Classes
    Any

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

    Permalink
    Definition Classes
    BoostingParams

  7. val baseLearner: Param[EnsemblePredictorType]

    Permalink

    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

    Permalink
    Definition Classes
    BoostingParams

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

    Permalink
    Definition Classes
    Params

  10. def clone(): AnyRef

    Permalink
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  11. def copy(extra: ParamMap): BoostingRegressor

    Permalink
    Definition Classes
    BoostingRegressor → Predictor → Estimator → PipelineStage → Params

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

    Permalink
    Attributes
    protected
    Definition Classes
    Params

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

    Permalink
    Attributes
    protected
    Definition Classes
    Params

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

    Permalink
    Definition Classes
    AnyRef

  15. def equals(arg0: Any): Boolean

    Permalink
    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

    Permalink
    Definition Classes
    BoostingParams

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

    Permalink
    Definition Classes
    BoostingParams

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

    Permalink
    Definition Classes
    Params

  19. def explainParams(): String

    Permalink
    Definition Classes
    Params

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

    Permalink
    Definition Classes
    BoostingParams

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

    Permalink
    Attributes
    protected
    Definition Classes
    Predictor

  22. final def extractParamMap(): ParamMap

    Permalink
    Definition Classes
    Params

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

    Permalink
    Definition Classes
    Params

  24. final val featuresCol: Param[String]

    Permalink
    Definition Classes
    HasFeaturesCol

  25. def finalize(): Unit

    Permalink
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

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

    Permalink
    Definition Classes
    Predictor → Estimator

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

    Permalink
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )

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

    Permalink
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )

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

    Permalink
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()

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

    Permalink
    Definition Classes
    HasBaseLearner

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

    Permalink
    Definition Classes
    Params

  32. def getBaseLearner: EnsemblePredictorType

    Permalink

    Definition Classes
    HasBaseLearner

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

    Permalink
    Definition Classes
    AnyRef → Any

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

    Permalink
    Definition Classes
    Params

  35. final def getFeaturesCol: String

    Permalink
    Definition Classes
    HasFeaturesCol

  36. final def getLabelCol: String

    Permalink
    Definition Classes
    HasLabelCol

  37. def getLoss: String

    Permalink

    Definition Classes
    BoostingRegressorParams

  38. def getNumBaseLearners: Int

    Permalink

    Definition Classes
    HasNumBaseLearners

  39. def getNumRound: Int

    Permalink

    Definition Classes
    HasNumRound

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

    Permalink
    Definition Classes
    Params

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

    Permalink
    Definition Classes
    Params

  42. final def getPredictionCol: String

    Permalink
    Definition Classes
    HasPredictionCol

  43. final def getSeed: Long

    Permalink
    Definition Classes
    HasSeed

  44. final def getTol: Double

    Permalink
    Definition Classes
    HasTol

  45. final def getValidationIndicatorCol: String

    Permalink
    Definition Classes
    HasValidationIndicatorCol

  46. final def getWeightCol: String

    Permalink
    Definition Classes
    HasWeightCol

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

    Permalink
    Definition Classes
    Params

  48. def hasParam(paramName: String): Boolean

    Permalink
    Definition Classes
    Params

  49. def hashCode(): Int

    Permalink
    Definition Classes
    AnyRef → Any

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

    Permalink
    Attributes
    protected
    Definition Classes
    Logging

  51. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

    Permalink
    Attributes
    protected
    Definition Classes
    Logging

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

    Permalink
    Definition Classes
    Params

  53. final def isInstanceOf[T0]: Boolean

    Permalink
    Definition Classes
    Any

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

    Permalink
    Definition Classes
    Params

  55. def isTraceEnabled(): Boolean

    Permalink
    Attributes
    protected
    Definition Classes
    Logging

  56. final val labelCol: Param[String]

    Permalink
    Definition Classes
    HasLabelCol

  57. def log: Logger

    Permalink
    Attributes
    protected
    Definition Classes
    Logging

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

    Permalink
    Attributes
    protected
    Definition Classes
    Logging

  59. def logDebug(msg: ⇒ String): Unit

    Permalink
    Attributes
    protected
    Definition Classes
    Logging

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

    Permalink
    Attributes
    protected
    Definition Classes
    Logging

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

    Permalink
    Attributes
    protected
    Definition Classes
    Logging

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

    Permalink
    Attributes
    protected
    Definition Classes
    Logging

  63. def logInfo(msg: ⇒ String): Unit

    Permalink
    Attributes
    protected
    Definition Classes
    Logging

  64. def logName: String

    Permalink
    Attributes
    protected
    Definition Classes
    Logging

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

    Permalink
    Attributes
    protected
    Definition Classes
    Logging

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

    Permalink
    Attributes
    protected
    Definition Classes
    Logging

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

    Permalink
    Attributes
    protected
    Definition Classes
    Logging

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

    Permalink
    Attributes
    protected
    Definition Classes
    Logging

  69. val loss: Param[String]

    Permalink

    Loss function which Boosting tries to minimize.

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

    Definition Classes
    BoostingRegressorParams

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

    Permalink
    Definition Classes
    AnyRef

  71. final def notify(): Unit

    Permalink
    Definition Classes
    AnyRef

  72. final def notifyAll(): Unit

    Permalink
    Definition Classes
    AnyRef

  73. val numBaseLearners: Param[Int]

    Permalink

    param for the number of base learners of the algorithm

    param for the number of base learners of the algorithm

    Definition Classes
    HasNumBaseLearners

  74. val numRound: Param[Int]

    Permalink

    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

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

    Permalink
    Definition Classes
    Params

  76. final val predictionCol: Param[String]

    Permalink
    Definition Classes
    HasPredictionCol

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

    Permalink
    Definition Classes
    BoostingParams

  78. def save(path: String): Unit

    Permalink
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )

  79. final val seed: LongParam

    Permalink
    Definition Classes
    HasSeed

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

    Permalink
    Attributes
    protected
    Definition Classes
    Params

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

    Permalink
    Attributes
    protected
    Definition Classes
    Params

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

    Permalink
    Definition Classes
    Params

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

    Permalink

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

    Permalink
    Attributes
    protected
    Definition Classes
    Params

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

    Permalink
    Attributes
    protected
    Definition Classes
    Params

  86. def setFeaturesCol(value: String): BoostingRegressor

    Permalink
    Definition Classes
    Predictor

  87. def setLabelCol(value: String): BoostingRegressor

    Permalink
    Definition Classes
    Predictor

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

    Permalink

  89. def setNumBaseLearners(value: Int): BoostingRegressor.this.type

    Permalink

  90. def setNumRound(value: Int): BoostingRegressor.this.type

    Permalink

  91. def setPredictionCol(value: String): BoostingRegressor

    Permalink
    Definition Classes
    Predictor

  92. def setSeed(value: Long): BoostingRegressor.this.type

    Permalink

  93. def setTol(value: Double): BoostingRegressor.this.type

    Permalink

  94. def setValidationIndicatorCol(value: String): BoostingRegressor.this.type

    Permalink

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

    Permalink

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

    Permalink
    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)

    Permalink
    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)

    Permalink
    Definition Classes
    BoostingParams

  99. def toString(): String

    Permalink
    Definition Classes
    Identifiable → AnyRef → Any

  100. final val tol: DoubleParam

    Permalink
    Definition Classes
    HasTol

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

    Permalink
    Attributes
    protected
    Definition Classes
    BoostingRegressor → Predictor

  102. def transformSchema(schema: StructType): StructType

    Permalink
    Definition Classes
    Predictor → PipelineStage

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

    Permalink
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()

  104. val uid: String

    Permalink
    Definition Classes
    BoostingRegressor → Identifiable

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

    Permalink
    Definition Classes
    BoostingParams

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

    Permalink
    Attributes
    protected
    Definition Classes
    PredictorParams

  107. final val validationIndicatorCol: Param[String]

    Permalink
    Definition Classes
    HasValidationIndicatorCol

  108. final def wait(): Unit

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  111. def weight(beta: Double): Double

    Permalink
    Definition Classes
    BoostingParams

  112. final val weightCol: Param[String]

    Permalink
    Definition Classes
    HasWeightCol

  113. def write: MLWriter

    Permalink
    Definition Classes
    BoostingRegressor → MLWritable

Inherited from MLWritable

Inherited from BoostingRegressorParams

Inherited from BoostingParams

Inherited from HasNumRound

Inherited from HasTol

Inherited from HasValidationIndicatorCol

Inherited from HasBaseLearner

Inherited from HasSeed

Inherited from HasWeightCol

Inherited from HasNumBaseLearners

Inherited from Predictor[Vector, BoostingRegressor, BoostingRegressionModel]

Inherited from PredictorParams

Inherited from HasPredictionCol

Inherited from HasFeaturesCol

Inherited from HasLabelCol

Inherited from Estimator[BoostingRegressionModel]

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

getParam

param

setParam

Ungrouped