class BaggingClassifier extends ProbabilisticClassifier[Vector, BaggingClassifier, BaggingClassificationModel] with BaggingClassifierParams with MLWritable

Source
BaggingClassifier.scala
Linear Supertypes
MLWritable, BaggingClassifierParams, BaggingParams[EnsembleClassifierType], HasSubBag, HasSeed, HasBaseLearner[EnsembleClassifierType], HasWeightCol, HasParallelism, HasNumBaseLearners, ProbabilisticClassifier[Vector, BaggingClassifier, BaggingClassificationModel], ProbabilisticClassifierParams, HasThresholds, HasProbabilityCol, Classifier[Vector, BaggingClassifier, BaggingClassificationModel], ClassifierParams, HasRawPredictionCol, Predictor[Vector, BaggingClassifier, BaggingClassificationModel], PredictorParams, HasPredictionCol, HasFeaturesCol, HasLabelCol, Estimator[BaggingClassificationModel], PipelineStage, Logging, Params, Serializable, Identifiable, AnyRef, Any
Ordering
  1. Grouped
  2. Alphabetic
  3. By Inheritance
Inherited
  1. BaggingClassifier
  2. MLWritable
  3. BaggingClassifierParams
  4. BaggingParams
  5. HasSubBag
  6. HasSeed
  7. HasBaseLearner
  8. HasWeightCol
  9. HasParallelism
  10. HasNumBaseLearners
  11. ProbabilisticClassifier
  12. ProbabilisticClassifierParams
  13. HasThresholds
  14. HasProbabilityCol
  15. Classifier
  16. ClassifierParams
  17. HasRawPredictionCol
  18. Predictor
  19. PredictorParams
  20. HasPredictionCol
  21. HasFeaturesCol
  22. HasLabelCol
  23. Estimator
  24. PipelineStage
  25. Logging
  26. Params
  27. Serializable
  28. Identifiable
  29. AnyRef
  30. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. Protected

Instance Constructors

  1. new BaggingClassifier()
  2. new BaggingClassifier(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 def asInstanceOf[T0]: T0
    Definition Classes
    Any
  6. 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
  7. final def clear(param: Param[_]): BaggingClassifier.this.type
    Definition Classes
    Params
  8. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.CloneNotSupportedException]) @native()
  9. def copy(extra: ParamMap): BaggingClassifier
    Definition Classes
    BaggingClassifier → 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: AnyRef): Boolean
    Definition Classes
    AnyRef → Any
  14. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  15. def explainParams(): String
    Definition Classes
    Params
  16. def extractInstances(dataset: Dataset[_], numClasses: Int): RDD[Instance]
    Attributes
    protected
    Definition Classes
    ClassifierParams
  17. def extractInstances(dataset: Dataset[_], validateInstance: (Instance) => Unit): RDD[Instance]
    Attributes
    protected
    Definition Classes
    PredictorParams
  18. def extractInstances(dataset: Dataset[_]): RDD[Instance]
    Attributes
    protected
    Definition Classes
    PredictorParams
  19. def extractLabeledPoints(dataset: Dataset[_], numClasses: Int): RDD[LabeledPoint]
    Attributes
    protected
    Definition Classes
    Classifier
  20. def extractLabeledPoints(dataset: Dataset[_]): RDD[LabeledPoint]
    Attributes
    protected
    Definition Classes
    Predictor
  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 finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.Throwable])
  25. def fit(dataset: Dataset[_]): BaggingClassificationModel
    Definition Classes
    Predictor → Estimator
  26. def fit(dataset: Dataset[_], paramMaps: Seq[ParamMap]): Seq[BaggingClassificationModel]
    Definition Classes
    Estimator
    Annotations
    @Since("2.0.0")
  27. def fit(dataset: Dataset[_], paramMap: ParamMap): BaggingClassificationModel
    Definition Classes
    Estimator
    Annotations
    @Since("2.0.0")
  28. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): BaggingClassificationModel
    Definition Classes
    Estimator
    Annotations
    @Since("2.0.0") @varargs()
  29. def fitBaseLearner(baseLearner: EnsembleClassifierType, labelColName: String, featuresColName: String, predictionColName: String, weightColName: Option[String])(df: DataFrame): EnsemblePredictionModelType
    Attributes
    protected
    Definition Classes
    HasBaseLearner
  30. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  31. def getBaseLearner: EnsembleClassifierType

    Definition Classes
    HasBaseLearner
  32. final def getClass(): Class[_ <: AnyRef]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  33. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  34. final def getFeaturesCol: String
    Definition Classes
    HasFeaturesCol
  35. final def getLabelCol: String
    Definition Classes
    HasLabelCol
  36. def getNumBaseLearners: Int

    Definition Classes
    HasNumBaseLearners
  37. def getNumClasses(dataset: Dataset[_], maxNumClasses: Int): Int
    Attributes
    protected
    Definition Classes
    Classifier
  38. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  39. def getParallelism: Int
    Definition Classes
    HasParallelism
  40. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  41. final def getPredictionCol: String
    Definition Classes
    HasPredictionCol
  42. final def getProbabilityCol: String
    Definition Classes
    HasProbabilityCol
  43. final def getRawPredictionCol: String
    Definition Classes
    HasRawPredictionCol
  44. def getReplacement: Boolean

    Definition Classes
    HasSubBag
  45. final def getSeed: Long
    Definition Classes
    HasSeed
  46. def getSubsampleRatio: Double

    Definition Classes
    HasSubBag
  47. def getSubspaceRatio: Double

    Definition Classes
    HasSubBag
  48. def getThresholds: Array[Double]
    Definition Classes
    HasThresholds
  49. def getVotingStrategy: String

    Definition Classes
    BaggingClassifierParams
  50. final def getWeightCol: String
    Definition Classes
    HasWeightCol
  51. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  52. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  53. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  54. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  55. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  56. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  57. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  58. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  59. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  60. final val labelCol: Param[String]
    Definition Classes
    HasLabelCol
  61. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  62. def logDebug(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  63. def logDebug(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  64. def logError(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  65. def logError(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  66. def logInfo(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  67. def logInfo(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  68. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  69. def logTrace(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  70. def logTrace(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  71. def logWarning(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  72. def logWarning(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  73. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  74. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  75. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  76. 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
  77. val parallelism: IntParam
    Definition Classes
    HasParallelism
  78. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  79. final val predictionCol: Param[String]
    Definition Classes
    HasPredictionCol
  80. final val probabilityCol: Param[String]
    Definition Classes
    HasProbabilityCol
  81. final val rawPredictionCol: Param[String]
    Definition Classes
    HasRawPredictionCol
  82. val replacement: Param[Boolean]

    param for whether samples are drawn with replacement

    param for whether samples are drawn with replacement

    Definition Classes
    HasSubBag
  83. 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.")
  84. final val seed: LongParam
    Definition Classes
    HasSeed
  85. final def set(paramPair: ParamPair[_]): BaggingClassifier.this.type
    Attributes
    protected
    Definition Classes
    Params
  86. final def set(param: String, value: Any): BaggingClassifier.this.type
    Attributes
    protected
    Definition Classes
    Params
  87. final def set[T](param: Param[T], value: T): BaggingClassifier.this.type
    Definition Classes
    Params
  88. def setBaseLearner(value: EnsembleClassifierType): BaggingClassifier.this.type

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

  94. def setParallelism(value: Int): BaggingClassifier.this.type

    Set the maximum level of parallelism to evaluate models in parallel.

    Set the maximum level of parallelism to evaluate models in parallel. Default is 1 for serial evaluation

  95. def setPredictionCol(value: String): BaggingClassifier
    Definition Classes
    Predictor
  96. def setProbabilityCol(value: String): BaggingClassifier
    Definition Classes
    ProbabilisticClassifier
  97. def setRawPredictionCol(value: String): BaggingClassifier
    Definition Classes
    Classifier
  98. def setReplacement(value: Boolean): BaggingClassifier.this.type

  99. def setSubsampleRatio(value: Double): BaggingClassifier.this.type

  100. def setSubspaceRatio(value: Double): BaggingClassifier.this.type

  101. def setThresholds(value: Array[Double]): BaggingClassifier
    Definition Classes
    ProbabilisticClassifier
  102. def setVotingStrategy(value: String): BaggingClassifier.this.type

  103. def setWeightCol(value: String): BaggingClassifier.this.type

  104. def slice(indices: Array[Int]): (Vector) => Vector
    Attributes
    protected
    Definition Classes
    HasSubBag
  105. val subsampleRatio: 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
  106. def subspace(subspaceRatio: Double, numFeatures: Int, seed: Long): Array[Int]
    Attributes
    protected
    Definition Classes
    HasSubBag
  107. 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
  108. final def synchronized[T0](arg0: => T0): T0
    Definition Classes
    AnyRef
  109. val thresholds: DoubleArrayParam
    Definition Classes
    HasThresholds
  110. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  111. def train(dataset: Dataset[_]): BaggingClassificationModel
    Attributes
    protected
    Definition Classes
    BaggingClassifier → Predictor
  112. def transformSchema(schema: StructType): StructType
    Definition Classes
    Predictor → PipelineStage
  113. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  114. val uid: String
    Definition Classes
    BaggingClassifier → Identifiable
  115. def validateAndTransformSchema(schema: StructType, fitting: Boolean, featuresDataType: DataType): StructType
    Attributes
    protected
    Definition Classes
    ProbabilisticClassifierParams → ClassifierParams → PredictorParams
  116. def validateLabel(label: Double, numClasses: Int): Unit
    Attributes
    protected
    Definition Classes
    Classifier
  117. def validateNumClasses(numClasses: Int): Unit
    Attributes
    protected
    Definition Classes
    Classifier
  118. val votingStrategy: Param[String]

    Voting strategy to aggregate predictions of base classifiers.

    Voting strategy to aggregate predictions of base classifiers. (case-insensitive) Supported: "hard", "soft". (default = hard)

    Definition Classes
    BaggingClassifierParams
  119. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  120. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  121. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException]) @native()
  122. final val weightCol: Param[String]
    Definition Classes
    HasWeightCol
  123. def write: MLWriter
    Definition Classes
    BaggingClassifier → MLWritable

Inherited from MLWritable

Inherited from BaggingClassifierParams

Inherited from BaggingParams[EnsembleClassifierType]

Inherited from HasSubBag

Inherited from HasSeed

Inherited from HasBaseLearner[EnsembleClassifierType]

Inherited from HasWeightCol

Inherited from HasParallelism

Inherited from HasNumBaseLearners

Inherited from ProbabilisticClassifier[Vector, BaggingClassifier, BaggingClassificationModel]

Inherited from ProbabilisticClassifierParams

Inherited from HasThresholds

Inherited from HasProbabilityCol

Inherited from Classifier[Vector, BaggingClassifier, BaggingClassificationModel]

Inherited from ClassifierParams

Inherited from HasRawPredictionCol

Inherited from Predictor[Vector, BaggingClassifier, BaggingClassificationModel]

Inherited from PredictorParams

Inherited from HasPredictionCol

Inherited from HasFeaturesCol

Inherited from HasLabelCol

Inherited from Estimator[BaggingClassificationModel]

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

expertSetParam

getParam

param

setParam

Ungrouped