Class/Object

org.apache.spark.ml.classification

BaggingClassifier

Related Docs: object BaggingClassifier | package classification

Permalink

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

Linear Supertypes
MLWritable, BaggingClassifierParams, ClassifierParams, HasRawPredictionCol, BaggingParams, SubSpaceParams, HasSeed, HasBaseLearner, HasWeightCol, HasParallelism, HasMaxIter, Predictor[Vector, BaggingClassifier, BaggingClassificationModel], PredictorParams, HasPredictionCol, HasFeaturesCol, HasLabelCol, Estimator[BaggingClassificationModel], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. BaggingClassifier
  2. MLWritable
  3. BaggingClassifierParams
  4. ClassifierParams
  5. HasRawPredictionCol
  6. BaggingParams
  7. SubSpaceParams
  8. HasSeed
  9. HasBaseLearner
  10. HasWeightCol
  11. HasParallelism
  12. HasMaxIter
  13. Predictor
  14. PredictorParams
  15. HasPredictionCol
  16. HasFeaturesCol
  17. HasLabelCol
  18. Estimator
  19. PipelineStage
  20. Logging
  21. Params
  22. Serializable
  23. Serializable
  24. Identifiable
  25. AnyRef
  26. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Instance Constructors

  1. new BaggingClassifier()

    Permalink
  2. new BaggingClassifier(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. 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
  7. final def clear(param: Param[_]): BaggingClassifier.this.type

    Permalink
    Definition Classes
    Params
  8. def clone(): AnyRef

    Permalink
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  9. def copy(extra: ParamMap): BaggingClassifier

    Permalink
    Definition Classes
    BaggingClassifier → Predictor → Estimator → PipelineStage → Params
  10. def copyValues[T <: Params](to: T, extra: ParamMap): T

    Permalink
    Attributes
    protected
    Definition Classes
    Params
  11. final def defaultCopy[T <: Params](extra: ParamMap): T

    Permalink
    Attributes
    protected
    Definition Classes
    Params
  12. final def eq(arg0: AnyRef): Boolean

    Permalink
    Definition Classes
    AnyRef
  13. def equals(arg0: Any): Boolean

    Permalink
    Definition Classes
    AnyRef → Any
  14. def explainParam(param: Param[_]): String

    Permalink
    Definition Classes
    Params
  15. def explainParams(): String

    Permalink
    Definition Classes
    Params
  16. def extractLabeledPoints(dataset: Dataset[_]): RDD[LabeledPoint]

    Permalink
    Attributes
    protected
    Definition Classes
    Predictor
  17. final def extractParamMap(): ParamMap

    Permalink
    Definition Classes
    Params
  18. final def extractParamMap(extra: ParamMap): ParamMap

    Permalink
    Definition Classes
    Params
  19. final val featuresCol: Param[String]

    Permalink
    Definition Classes
    HasFeaturesCol
  20. def finalize(): Unit

    Permalink
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  21. def fit(dataset: Dataset[_]): BaggingClassificationModel

    Permalink
    Definition Classes
    Predictor → Estimator
  22. def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[BaggingClassificationModel]

    Permalink
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  23. def fit(dataset: Dataset[_], paramMap: ParamMap): BaggingClassificationModel

    Permalink
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  24. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): BaggingClassificationModel

    Permalink
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()
  25. final def get[T](param: Param[T]): Option[T]

    Permalink
    Definition Classes
    Params
  26. def getBaseLearner: EnsemblePredictorType

    Permalink

    Definition Classes
    HasBaseLearner
  27. final def getClass(): Class[_]

    Permalink
    Definition Classes
    AnyRef → Any
  28. final def getDefault[T](param: Param[T]): Option[T]

    Permalink
    Definition Classes
    Params
  29. final def getFeaturesCol: String

    Permalink
    Definition Classes
    HasFeaturesCol
  30. final def getLabelCol: String

    Permalink
    Definition Classes
    HasLabelCol
  31. final def getMaxIter: Int

    Permalink
    Definition Classes
    HasMaxIter
  32. final def getOrDefault[T](param: Param[T]): T

    Permalink
    Definition Classes
    Params
  33. def getParallelism: Int

    Permalink
    Definition Classes
    HasParallelism
  34. def getParam(paramName: String): Param[Any]

    Permalink
    Definition Classes
    Params
  35. final def getPredictionCol: String

    Permalink
    Definition Classes
    HasPredictionCol
  36. final def getRawPredictionCol: String

    Permalink
    Definition Classes
    HasRawPredictionCol
  37. def getReplacement: Boolean

    Permalink

    Definition Classes
    SubSpaceParams
  38. def getReplacementFeatures: Boolean

    Permalink

    Definition Classes
    SubSpaceParams
  39. def getSampleRatio: Double

    Permalink

    Definition Classes
    SubSpaceParams
  40. def getSampleRatioFeatures: Double

    Permalink

    Definition Classes
    SubSpaceParams
  41. final def getSeed: Long

    Permalink
    Definition Classes
    HasSeed
  42. final def getWeightCol: String

    Permalink
    Definition Classes
    HasWeightCol
  43. final def hasDefault[T](param: Param[T]): Boolean

    Permalink
    Definition Classes
    Params
  44. def hasParam(paramName: String): Boolean

    Permalink
    Definition Classes
    Params
  45. def hashCode(): Int

    Permalink
    Definition Classes
    AnyRef → Any
  46. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  47. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  48. final def isDefined(param: Param[_]): Boolean

    Permalink
    Definition Classes
    Params
  49. final def isInstanceOf[T0]: Boolean

    Permalink
    Definition Classes
    Any
  50. final def isSet(param: Param[_]): Boolean

    Permalink
    Definition Classes
    Params
  51. def isTraceEnabled(): Boolean

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  52. final val labelCol: Param[String]

    Permalink
    Definition Classes
    HasLabelCol
  53. def log: Logger

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  54. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  55. def logDebug(msg: ⇒ String): Unit

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  56. def logError(msg: ⇒ String, throwable: Throwable): Unit

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  57. def logError(msg: ⇒ String): Unit

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  58. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  59. def logInfo(msg: ⇒ String): Unit

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  60. def logName: String

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  61. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  62. def logTrace(msg: ⇒ String): Unit

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  63. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  64. def logWarning(msg: ⇒ String): Unit

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  65. final val maxIter: IntParam

    Permalink
    Definition Classes
    HasMaxIter
  66. final def ne(arg0: AnyRef): Boolean

    Permalink
    Definition Classes
    AnyRef
  67. final def notify(): Unit

    Permalink
    Definition Classes
    AnyRef
  68. final def notifyAll(): Unit

    Permalink
    Definition Classes
    AnyRef
  69. val parallelism: IntParam

    Permalink
    Definition Classes
    HasParallelism
  70. lazy val params: Array[Param[_]]

    Permalink
    Definition Classes
    Params
  71. final val predictionCol: Param[String]

    Permalink
    Definition Classes
    HasPredictionCol
  72. final val rawPredictionCol: Param[String]

    Permalink
    Definition Classes
    HasRawPredictionCol
  73. val replacement: Param[Boolean]

    Permalink

    param for whether samples are drawn with replacement

    param for whether samples are drawn with replacement

    Definition Classes
    SubSpaceParams
  74. val replacementFeatures: Param[Boolean]

    Permalink

    param for whether samples are drawn with replacement

    param for whether samples are drawn with replacement

    Definition Classes
    SubSpaceParams
  75. val sampleRatio: Param[Double]

    Permalink

    param for ratio of rows sampled out of the dataset

    param for ratio of rows sampled out of the dataset

    Definition Classes
    SubSpaceParams
  76. val sampleRatioFeatures: Param[Double]

    Permalink

    param for ratio of rows sampled out of the dataset

    param for ratio of rows sampled out of the dataset

    Definition Classes
    SubSpaceParams
  77. def save(path: String): Unit

    Permalink
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  78. final val seed: LongParam

    Permalink
    Definition Classes
    HasSeed
  79. final def set(paramPair: ParamPair[_]): BaggingClassifier.this.type

    Permalink
    Attributes
    protected
    Definition Classes
    Params
  80. final def set(param: String, value: Any): BaggingClassifier.this.type

    Permalink
    Attributes
    protected
    Definition Classes
    Params
  81. final def set[T](param: Param[T], value: T): BaggingClassifier.this.type

    Permalink
    Definition Classes
    Params
  82. def setBaseLearner(value: Predictor[_, _, _]): BaggingClassifier.this.type

    Permalink

  83. final def setDefault(paramPairs: ParamPair[_]*): BaggingClassifier.this.type

    Permalink
    Attributes
    protected
    Definition Classes
    Params
  84. final def setDefault[T](param: Param[T], value: T): BaggingClassifier.this.type

    Permalink
    Attributes
    protected
    Definition Classes
    Params
  85. def setFeaturesCol(value: String): BaggingClassifier

    Permalink
    Definition Classes
    Predictor
  86. def setLabelCol(value: String): BaggingClassifier

    Permalink
    Definition Classes
    Predictor
  87. def setMaxIter(value: Int): BaggingClassifier.this.type

    Permalink

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

    Permalink

    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

  89. def setPredictionCol(value: String): BaggingClassifier

    Permalink
    Definition Classes
    Predictor
  90. def setReplacement(value: Boolean): BaggingClassifier.this.type

    Permalink

  91. def setReplacementFeatures(value: Boolean): BaggingClassifier.this.type

    Permalink

  92. def setSampleRatio(value: Double): BaggingClassifier.this.type

    Permalink

  93. def setSampleRatioFeatures(value: Double): BaggingClassifier.this.type

    Permalink

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

    Permalink

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

    Permalink
    Definition Classes
    AnyRef
  96. def toString(): String

    Permalink
    Definition Classes
    Identifiable → AnyRef → Any
  97. def train(dataset: Dataset[_]): BaggingClassificationModel

    Permalink
    Attributes
    protected
    Definition Classes
    BaggingClassifier → Predictor
  98. def transformSchema(schema: StructType): StructType

    Permalink
    Definition Classes
    Predictor → PipelineStage
  99. def transformSchema(schema: StructType, logging: Boolean): StructType

    Permalink
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  100. val uid: String

    Permalink
    Definition Classes
    BaggingClassifier → Identifiable
  101. def validateAndTransformSchema(schema: StructType, fitting: Boolean, featuresDataType: DataType): StructType

    Permalink
    Attributes
    protected
    Definition Classes
    ClassifierParams → PredictorParams
  102. final def wait(): Unit

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  103. final def wait(arg0: Long, arg1: Int): Unit

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  104. final def wait(arg0: Long): Unit

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  105. final val weightCol: Param[String]

    Permalink
    Definition Classes
    HasWeightCol
  106. def write: MLWriter

    Permalink
    Definition Classes
    BaggingClassifier → MLWritable

Inherited from MLWritable

Inherited from BaggingClassifierParams

Inherited from ClassifierParams

Inherited from HasRawPredictionCol

Inherited from BaggingParams

Inherited from SubSpaceParams

Inherited from HasSeed

Inherited from HasBaseLearner

Inherited from HasWeightCol

Inherited from HasParallelism

Inherited from HasMaxIter

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 Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

expertSetParam

getParam

param

setParam

Ungrouped