class BoostingClassifier extends Classifier[Vector, BoostingClassifier, BoostingClassificationModel] with BoostingClassifierParams with MLWritable

Source
BoostingClassifier.scala
Linear Supertypes
MLWritable, BoostingClassifierParams, BoostingParams[EnsembleClassifierType], HasAggregationDepth, HasCheckpointInterval, HasBaseLearner[EnsembleClassifierType], HasWeightCol, HasNumBaseLearners, Classifier[Vector, BoostingClassifier, BoostingClassificationModel], ClassifierParams, HasRawPredictionCol, Predictor[Vector, BoostingClassifier, BoostingClassificationModel], PredictorParams, HasPredictionCol, HasFeaturesCol, HasLabelCol, Estimator[BoostingClassificationModel], PipelineStage, Logging, Params, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. BoostingClassifier
  2. MLWritable
  3. BoostingClassifierParams
  4. BoostingParams
  5. HasAggregationDepth
  6. HasCheckpointInterval
  7. HasBaseLearner
  8. HasWeightCol
  9. HasNumBaseLearners
  10. Classifier
  11. ClassifierParams
  12. HasRawPredictionCol
  13. Predictor
  14. PredictorParams
  15. HasPredictionCol
  16. HasFeaturesCol
  17. HasLabelCol
  18. Estimator
  19. PipelineStage
  20. Logging
  21. Params
  22. Serializable
  23. Identifiable
  24. AnyRef
  25. Any
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Visibility
  1. Public
  2. Protected

Instance Constructors

  1. new BoostingClassifier()
  2. new BoostingClassifier(uid: String)

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 val aggregationDepth: IntParam
    Definition Classes
    HasAggregationDepth
  6. val algorithm: Param[String]

    Discrete (SAMME) or Real (SAMME.R) boosting algorithm.

    Discrete (SAMME) or Real (SAMME.R) boosting algorithm. (case-insensitive) Supported: "discrete", "real". (default = median)

    Definition Classes
    BoostingClassifierParams
  7. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  8. val baseLearner: Param[EnsembleClassifierType]

    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
  9. final val checkpointInterval: IntParam
    Definition Classes
    HasCheckpointInterval
  10. final def clear(param: Param[_]): BoostingClassifier.this.type
    Definition Classes
    Params
  11. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.CloneNotSupportedException]) @native()
  12. def copy(extra: ParamMap): BoostingClassifier
    Definition Classes
    BoostingClassifier → Predictor → Estimator → PipelineStage → Params
  13. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  14. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  15. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  16. def equals(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef → Any
  17. def error(label: Double, prediction: Double): Double
  18. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  19. def explainParams(): String
    Definition Classes
    Params
  20. def extractInstances(dataset: Dataset[_], numClasses: Int): RDD[Instance]
    Attributes
    protected
    Definition Classes
    ClassifierParams
  21. def extractInstances(dataset: Dataset[_], validateInstance: (Instance) => Unit): RDD[Instance]
    Attributes
    protected
    Definition Classes
    PredictorParams
  22. def extractInstances(dataset: Dataset[_]): RDD[Instance]
    Attributes
    protected
    Definition Classes
    PredictorParams
  23. def extractLabeledPoints(dataset: Dataset[_], numClasses: Int): RDD[LabeledPoint]
    Attributes
    protected
    Definition Classes
    Classifier
  24. def extractLabeledPoints(dataset: Dataset[_]): RDD[LabeledPoint]
    Attributes
    protected
    Definition Classes
    Predictor
  25. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  26. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  27. final val featuresCol: Param[String]
    Definition Classes
    HasFeaturesCol
  28. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.Throwable])
  29. def fit(dataset: Dataset[_]): BoostingClassificationModel
    Definition Classes
    Predictor → Estimator
  30. def fit(dataset: Dataset[_], paramMaps: Seq[ParamMap]): Seq[BoostingClassificationModel]
    Definition Classes
    Estimator
    Annotations
    @Since("2.0.0")
  31. def fit(dataset: Dataset[_], paramMap: ParamMap): BoostingClassificationModel
    Definition Classes
    Estimator
    Annotations
    @Since("2.0.0")
  32. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): BoostingClassificationModel
    Definition Classes
    Estimator
    Annotations
    @Since("2.0.0") @varargs()
  33. def fitBaseLearner(baseLearner: EnsembleClassifierType, labelColName: String, featuresColName: String, predictionColName: String, weightColName: Option[String])(df: DataFrame): EnsemblePredictionModelType
    Attributes
    protected
    Definition Classes
    HasBaseLearner
  34. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  35. final def getAggregationDepth: Int
    Definition Classes
    HasAggregationDepth
  36. def getAlgorithm: String

    Definition Classes
    BoostingClassifierParams
  37. def getBaseLearner: EnsembleClassifierType

    Definition Classes
    HasBaseLearner
  38. final def getCheckpointInterval: Int
    Definition Classes
    HasCheckpointInterval
  39. final def getClass(): Class[_ <: AnyRef]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  40. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  41. final def getFeaturesCol: String
    Definition Classes
    HasFeaturesCol
  42. final def getLabelCol: String
    Definition Classes
    HasLabelCol
  43. def getNumBaseLearners: Int

    Definition Classes
    HasNumBaseLearners
  44. def getNumClasses(dataset: Dataset[_], maxNumClasses: Int): Int
    Attributes
    protected
    Definition Classes
    Classifier
  45. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  46. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  47. final def getPredictionCol: String
    Definition Classes
    HasPredictionCol
  48. final def getRawPredictionCol: String
    Definition Classes
    HasRawPredictionCol
  49. final def getWeightCol: String
    Definition Classes
    HasWeightCol
  50. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  51. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  52. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  53. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  54. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  55. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  56. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  57. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  58. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  59. final val labelCol: Param[String]
    Definition Classes
    HasLabelCol
  60. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  61. def logDebug(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  62. def logDebug(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  63. def logError(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  64. def logError(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  65. def logInfo(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  66. def logInfo(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  67. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  68. def logTrace(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  69. def logTrace(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  70. def logWarning(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  71. def logWarning(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  72. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  73. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  74. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  75. 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
  76. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  77. final val predictionCol: Param[String]
    Definition Classes
    HasPredictionCol
  78. final val rawPredictionCol: Param[String]
    Definition Classes
    HasRawPredictionCol
  79. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since("1.6.0") @throws("If the input path already exists but overwrite is not enabled.")
  80. final def set(paramPair: ParamPair[_]): BoostingClassifier.this.type
    Attributes
    protected
    Definition Classes
    Params
  81. final def set(param: String, value: Any): BoostingClassifier.this.type
    Attributes
    protected
    Definition Classes
    Params
  82. final def set[T](param: Param[T], value: T): BoostingClassifier.this.type
    Definition Classes
    Params
  83. def setAlgorithm(value: String): BoostingClassifier.this.type

  84. def setBaseLearner(value: EnsembleClassifierType): BoostingClassifier.this.type
  85. def setCheckpointInterval(value: Int): BoostingClassifier.this.type

  86. final def setDefault(paramPairs: ParamPair[_]*): BoostingClassifier.this.type
    Attributes
    protected
    Definition Classes
    Params
  87. final def setDefault[T](param: Param[T], value: T): BoostingClassifier.this.type
    Attributes
    protected
    Definition Classes
    Params
  88. def setFeaturesCol(value: String): BoostingClassifier
    Definition Classes
    Predictor
  89. def setLabelCol(value: String): BoostingClassifier
    Definition Classes
    Predictor
  90. def setNumBaseLearners(value: Int): BoostingClassifier.this.type

  91. def setPredictionCol(value: String): BoostingClassifier
    Definition Classes
    Predictor
  92. def setRawPredictionCol(value: String): BoostingClassifier
    Definition Classes
    Classifier
  93. def setWeightCol(value: String): BoostingClassifier.this.type

  94. final def synchronized[T0](arg0: => T0): T0
    Definition Classes
    AnyRef
  95. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  96. def train(dataset: Dataset[_]): BoostingClassificationModel
    Attributes
    protected
    Definition Classes
    BoostingClassifier → Predictor
  97. def transformSchema(schema: StructType): StructType
    Definition Classes
    Predictor → PipelineStage
  98. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  99. val uid: String
    Definition Classes
    BoostingClassifier → Identifiable
  100. def validateAndTransformSchema(schema: StructType, fitting: Boolean, featuresDataType: DataType): StructType
    Attributes
    protected
    Definition Classes
    ClassifierParams → PredictorParams
  101. def validateLabel(label: Double, numClasses: Int): Unit
    Attributes
    protected
    Definition Classes
    Classifier
  102. def validateNumClasses(numClasses: Int): Unit
    Attributes
    protected
    Definition Classes
    Classifier
  103. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  104. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  105. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException]) @native()
  106. final val weightCol: Param[String]
    Definition Classes
    HasWeightCol
  107. def write: MLWriter
    Definition Classes
    BoostingClassifier → MLWritable

Inherited from MLWritable

Inherited from BoostingClassifierParams

Inherited from BoostingParams[EnsembleClassifierType]

Inherited from HasAggregationDepth

Inherited from HasCheckpointInterval

Inherited from HasBaseLearner[EnsembleClassifierType]

Inherited from HasWeightCol

Inherited from HasNumBaseLearners

Inherited from Classifier[Vector, BoostingClassifier, BoostingClassificationModel]

Inherited from ClassifierParams

Inherited from HasRawPredictionCol

Inherited from Predictor[Vector, BoostingClassifier, BoostingClassificationModel]

Inherited from PredictorParams

Inherited from HasPredictionCol

Inherited from HasFeaturesCol

Inherited from HasLabelCol

Inherited from Estimator[BoostingClassificationModel]

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

getParam

param

setParam

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