class BaggingClassificationModel extends ProbabilisticClassificationModel[Vector, BaggingClassificationModel] with BaggingClassifierParams with MLWritable

Source
BaggingClassifier.scala
Linear Supertypes
MLWritable, BaggingClassifierParams, BaggingParams[EnsembleClassifierType], HasSubBag, HasSeed, HasBaseLearner[EnsembleClassifierType], HasWeightCol, HasParallelism, HasNumBaseLearners, ProbabilisticClassificationModel[Vector, BaggingClassificationModel], ProbabilisticClassifierParams, HasThresholds, HasProbabilityCol, ClassificationModel[Vector, BaggingClassificationModel], ClassifierParams, HasRawPredictionCol, PredictionModel[Vector, BaggingClassificationModel], PredictorParams, HasPredictionCol, HasFeaturesCol, HasLabelCol, Model[BaggingClassificationModel], Transformer, PipelineStage, Logging, Params, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. BaggingClassificationModel
  2. MLWritable
  3. BaggingClassifierParams
  4. BaggingParams
  5. HasSubBag
  6. HasSeed
  7. HasBaseLearner
  8. HasWeightCol
  9. HasParallelism
  10. HasNumBaseLearners
  11. ProbabilisticClassificationModel
  12. ProbabilisticClassifierParams
  13. HasThresholds
  14. HasProbabilityCol
  15. ClassificationModel
  16. ClassifierParams
  17. HasRawPredictionCol
  18. PredictionModel
  19. PredictorParams
  20. HasPredictionCol
  21. HasFeaturesCol
  22. HasLabelCol
  23. Model
  24. Transformer
  25. PipelineStage
  26. Logging
  27. Params
  28. Serializable
  29. Identifiable
  30. AnyRef
  31. Any
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Visibility
  1. Public
  2. Protected

Instance Constructors

  1. new BaggingClassificationModel(numClasses: Int, subspaces: Array[Array[Int]], models: Array[EnsemblePredictionModelType])
  2. new BaggingClassificationModel(uid: String, numClasses: Int, subspaces: Array[Array[Int]], models: Array[EnsemblePredictionModelType])

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[_]): BaggingClassificationModel.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): BaggingClassificationModel
    Definition Classes
    BaggingClassificationModel → 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: 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. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  20. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  21. final val featuresCol: Param[String]
    Definition Classes
    HasFeaturesCol
  22. def featuresDataType: DataType
    Attributes
    protected
    Definition Classes
    PredictionModel
  23. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.Throwable])
  24. def fitBaseLearner(baseLearner: EnsembleClassifierType, labelColName: String, featuresColName: String, predictionColName: String, weightColName: Option[String])(df: DataFrame): EnsemblePredictionModelType
    Attributes
    protected
    Definition Classes
    HasBaseLearner
  25. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  26. def getBaseLearner: EnsembleClassifierType

    Definition Classes
    HasBaseLearner
  27. final def getClass(): Class[_ <: AnyRef]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  28. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  29. final def getFeaturesCol: String
    Definition Classes
    HasFeaturesCol
  30. final def getLabelCol: String
    Definition Classes
    HasLabelCol
  31. def getNumBaseLearners: Int

    Definition Classes
    HasNumBaseLearners
  32. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  33. def getParallelism: Int
    Definition Classes
    HasParallelism
  34. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  35. final def getPredictionCol: String
    Definition Classes
    HasPredictionCol
  36. final def getProbabilityCol: String
    Definition Classes
    HasProbabilityCol
  37. final def getRawPredictionCol: String
    Definition Classes
    HasRawPredictionCol
  38. def getReplacement: Boolean

    Definition Classes
    HasSubBag
  39. final def getSeed: Long
    Definition Classes
    HasSeed
  40. def getSubsampleRatio: Double

    Definition Classes
    HasSubBag
  41. def getSubspaceRatio: Double

    Definition Classes
    HasSubBag
  42. def getThresholds: Array[Double]
    Definition Classes
    HasThresholds
  43. def getVotingStrategy: String

    Definition Classes
    BaggingClassifierParams
  44. final def getWeightCol: String
    Definition Classes
    HasWeightCol
  45. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  46. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  47. def hasParent: Boolean
    Definition Classes
    Model
  48. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  49. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  50. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  51. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  52. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  53. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  54. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  55. final val labelCol: Param[String]
    Definition Classes
    HasLabelCol
  56. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  57. def logDebug(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  58. def logDebug(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  59. def logError(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  60. def logError(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  61. def logInfo(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  62. def logInfo(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  63. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  64. def logTrace(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  65. def logTrace(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  66. def logWarning(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  67. def logWarning(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  68. val models: Array[EnsemblePredictionModelType]
  69. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  70. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  71. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  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 numClasses: Int
    Definition Classes
    BaggingClassificationModel → ClassificationModel
  74. def numFeatures: Int
    Definition Classes
    PredictionModel
    Annotations
    @Since("1.6.0")
  75. val numModels: Int
  76. val parallelism: IntParam
    Definition Classes
    HasParallelism
  77. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  78. var parent: Estimator[BaggingClassificationModel]
    Definition Classes
    Model
  79. def predict(features: Vector): Double
    Definition Classes
    ClassificationModel → PredictionModel
  80. def predictProbability(features: Vector): Vector
    Definition Classes
    ProbabilisticClassificationModel
    Annotations
    @Since("3.0.0")
  81. def predictRaw(features: Vector): Vector
    Definition Classes
    BaggingClassificationModel → ClassificationModel
  82. final val predictionCol: Param[String]
    Definition Classes
    HasPredictionCol
  83. def probability2prediction(probability: Vector): Double
    Attributes
    protected
    Definition Classes
    ProbabilisticClassificationModel
  84. final val probabilityCol: Param[String]
    Definition Classes
    HasProbabilityCol
  85. def raw2prediction(rawPrediction: Vector): Double
    Attributes
    protected
    Definition Classes
    ProbabilisticClassificationModel → ClassificationModel
  86. def raw2probability(rawPrediction: Vector): Vector
    Attributes
    protected
    Definition Classes
    ProbabilisticClassificationModel
  87. def raw2probabilityInPlace(rawPrediction: Vector): Vector
    Attributes
    protected
    Definition Classes
    BaggingClassificationModel → ProbabilisticClassificationModel
  88. final val rawPredictionCol: Param[String]
    Definition Classes
    HasRawPredictionCol
  89. val replacement: Param[Boolean]

    param for whether samples are drawn with replacement

    param for whether samples are drawn with replacement

    Definition Classes
    HasSubBag
  90. 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.")
  91. final val seed: LongParam
    Definition Classes
    HasSeed
  92. final def set(paramPair: ParamPair[_]): BaggingClassificationModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  93. final def set(param: String, value: Any): BaggingClassificationModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  94. final def set[T](param: Param[T], value: T): BaggingClassificationModel.this.type
    Definition Classes
    Params
  95. final def setDefault(paramPairs: ParamPair[_]*): BaggingClassificationModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  96. final def setDefault[T](param: Param[T], value: T): BaggingClassificationModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  97. def setFeaturesCol(value: String): BaggingClassificationModel
    Definition Classes
    PredictionModel
  98. def setParent(parent: Estimator[BaggingClassificationModel]): BaggingClassificationModel
    Definition Classes
    Model
  99. def setPredictionCol(value: String): BaggingClassificationModel
    Definition Classes
    PredictionModel
  100. def setProbabilityCol(value: String): BaggingClassificationModel
    Definition Classes
    ProbabilisticClassificationModel
  101. def setRawPredictionCol(value: String): BaggingClassificationModel
    Definition Classes
    ClassificationModel
  102. def setThresholds(value: Array[Double]): BaggingClassificationModel
    Definition Classes
    ProbabilisticClassificationModel
  103. def slice(indices: Array[Int]): (Vector) => Vector
    Attributes
    protected
    Definition Classes
    HasSubBag
  104. 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
  105. def subspace(subspaceRatio: Double, numFeatures: Int, seed: Long): Array[Int]
    Attributes
    protected
    Definition Classes
    HasSubBag
  106. 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
  107. val subspaces: Array[Array[Int]]
  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 transform(dataset: Dataset[_]): DataFrame
    Definition Classes
    ProbabilisticClassificationModel → ClassificationModel → PredictionModel → Transformer
  112. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since("2.0.0")
  113. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since("2.0.0") @varargs()
  114. final def transformImpl(dataset: Dataset[_]): DataFrame
    Definition Classes
    ClassificationModel → PredictionModel
  115. def transformSchema(schema: StructType): StructType
    Definition Classes
    ProbabilisticClassificationModel → ClassificationModel → PredictionModel → PipelineStage
  116. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  117. val uid: String
    Definition Classes
    BaggingClassificationModel → Identifiable
  118. def validateAndTransformSchema(schema: StructType, fitting: Boolean, featuresDataType: DataType): StructType
    Attributes
    protected
    Definition Classes
    ProbabilisticClassifierParams → ClassifierParams → PredictorParams
  119. 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
  120. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  121. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  122. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException]) @native()
  123. final val weightCol: Param[String]
    Definition Classes
    HasWeightCol
  124. def write: MLWriter
    Definition Classes
    BaggingClassificationModel → 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 ProbabilisticClassificationModel[Vector, BaggingClassificationModel]

Inherited from ProbabilisticClassifierParams

Inherited from HasThresholds

Inherited from HasProbabilityCol

Inherited from ClassificationModel[Vector, BaggingClassificationModel]

Inherited from ClassifierParams

Inherited from HasRawPredictionCol

Inherited from PredictionModel[Vector, BaggingClassificationModel]

Inherited from PredictorParams

Inherited from HasPredictionCol

Inherited from HasFeaturesCol

Inherited from HasLabelCol

Inherited from Model[BaggingClassificationModel]

Inherited from Transformer

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

getParam

param

Ungrouped