Class/Object

org.apache.spark.ml.classification

StackingClassifier

Related Docs: object StackingClassifier | package classification

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class StackingClassifier extends Predictor[Vector, StackingClassifier, StackingClassificationModel] with StackingClassifierParams with MLWritable

Linear Supertypes
MLWritable, StackingClassifierParams, ClassifierParams, HasRawPredictionCol, StackingParams, HasBaseLearners, HasStacker, HasWeightCol, HasParallelism, Predictor[Vector, StackingClassifier, StackingClassificationModel], PredictorParams, HasPredictionCol, HasFeaturesCol, HasLabelCol, Estimator[StackingClassificationModel], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. StackingClassifier
  2. MLWritable
  3. StackingClassifierParams
  4. ClassifierParams
  5. HasRawPredictionCol
  6. StackingParams
  7. HasBaseLearners
  8. HasStacker
  9. HasWeightCol
  10. HasParallelism
  11. Predictor
  12. PredictorParams
  13. HasPredictionCol
  14. HasFeaturesCol
  15. HasLabelCol
  16. Estimator
  17. PipelineStage
  18. Logging
  19. Params
  20. Serializable
  21. Serializable
  22. Identifiable
  23. AnyRef
  24. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new StackingClassifier()

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  2. new StackingClassifier(uid: String)

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Value Members

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

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    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any

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

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    Attributes
    protected
    Definition Classes
    Params

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

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    Definition Classes
    AnyRef → Any

  5. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  6. val baseLearners: Param[Array[EnsemblePredictorType]]

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    param for the estimators that will be used by the ensemble learner as base learners

    param for the estimators that will be used by the ensemble learner as base learners

    Definition Classes
    HasBaseLearners

  7. final def clear(param: Param[_]): StackingClassifier.this.type

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    Definition Classes
    Params

  8. def clone(): AnyRef

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

  9. def copy(extra: ParamMap): StackingClassifier

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    Definition Classes
    StackingClassifier → Predictor → Estimator → PipelineStage → Params

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

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    Attributes
    protected
    Definition Classes
    Params

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

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    Attributes
    protected
    Definition Classes
    Params

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

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    Definition Classes
    AnyRef

  13. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

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

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    Definition Classes
    Params

  15. def explainParams(): String

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    Definition Classes
    Params

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

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    Attributes
    protected
    Definition Classes
    Predictor

  17. final def extractParamMap(): ParamMap

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    Definition Classes
    Params

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

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    Definition Classes
    Params

  19. final val featuresCol: Param[String]

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    Definition Classes
    HasFeaturesCol

  20. def finalize(): Unit

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

  21. def fit(dataset: Dataset[_]): StackingClassificationModel

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    Definition Classes
    Predictor → Estimator

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

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )

  23. def fit(dataset: Dataset[_], paramMap: ParamMap): StackingClassificationModel

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )

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

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

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

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    Definition Classes
    HasBaseLearners

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

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    Definition Classes
    Params

  27. def getBaseLearners: Array[EnsemblePredictorType]

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    Definition Classes
    HasBaseLearners

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

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    Definition Classes
    AnyRef → Any

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

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    Definition Classes
    Params

  30. final def getFeaturesCol: String

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    Definition Classes
    HasFeaturesCol

  31. final def getLabelCol: String

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    Definition Classes
    HasLabelCol

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

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    Definition Classes
    Params

  33. def getParallelism: Int

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    Definition Classes
    HasParallelism

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

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    Definition Classes
    Params

  35. final def getPredictionCol: String

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    Definition Classes
    HasPredictionCol

  36. final def getRawPredictionCol: String

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    Definition Classes
    HasRawPredictionCol

  37. def getStacker: EnsemblePredictorType

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    Definition Classes
    HasStacker

  38. final def getWeightCol: String

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    Definition Classes
    HasWeightCol

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

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    Definition Classes
    Params

  40. def hasParam(paramName: String): Boolean

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    Definition Classes
    Params

  41. def hashCode(): Int

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    Definition Classes
    AnyRef → Any

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

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    Attributes
    protected
    Definition Classes
    Logging

  43. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Definition Classes
    Params

  45. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

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

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    Definition Classes
    Params

  47. def isTraceEnabled(): Boolean

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    Attributes
    protected
    Definition Classes
    Logging

  48. final val labelCol: Param[String]

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    Definition Classes
    HasLabelCol

  49. def log: Logger

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

  56. def logName: String

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Definition Classes
    AnyRef

  62. final def notify(): Unit

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    Definition Classes
    AnyRef

  63. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  64. val parallelism: IntParam

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    Definition Classes
    HasParallelism

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

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    Definition Classes
    Params

  66. final val predictionCol: Param[String]

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    Definition Classes
    HasPredictionCol

  67. final val rawPredictionCol: Param[String]

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    Definition Classes
    HasRawPredictionCol

  68. def save(path: String): Unit

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

  69. final def set(paramPair: ParamPair[_]): StackingClassifier.this.type

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    Attributes
    protected
    Definition Classes
    Params

  70. final def set(param: String, value: Any): StackingClassifier.this.type

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    Attributes
    protected
    Definition Classes
    Params

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

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    Definition Classes
    Params

  72. def setBaseLearners(value: Array[Predictor[_, _, _]]): StackingClassifier.this.type

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  73. final def setDefault(paramPairs: ParamPair[_]*): StackingClassifier.this.type

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    Attributes
    protected
    Definition Classes
    Params

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

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    Attributes
    protected
    Definition Classes
    Params

  75. def setFeaturesCol(value: String): StackingClassifier

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    Definition Classes
    Predictor

  76. def setLabelCol(value: String): StackingClassifier

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    Definition Classes
    Predictor

  77. def setParallelism(value: Int): StackingClassifier.this.type

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  78. def setPredictionCol(value: String): StackingClassifier

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    Definition Classes
    Predictor

  79. def setStacker(value: Predictor[_, _, _]): StackingClassifier.this.type

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  80. val stacker: Param[EnsemblePredictorType]

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    param for the estimator that will be used by the ensemble learner to aggregate results of base learner(s)

    param for the estimator that will be used by the ensemble learner to aggregate results of base learner(s)

    Definition Classes
    HasStacker

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

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    Definition Classes
    AnyRef

  82. def toString(): String

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    Definition Classes
    Identifiable → AnyRef → Any

  83. def train(dataset: Dataset[_]): StackingClassificationModel

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    Attributes
    protected
    Definition Classes
    StackingClassifier → Predictor

  84. def transformSchema(schema: StructType): StructType

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    Definition Classes
    Predictor → PipelineStage

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

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    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()

  86. val uid: String

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    Definition Classes
    StackingClassifier → Identifiable

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

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    Attributes
    protected
    Definition Classes
    ClassifierParams → PredictorParams

  88. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  91. final val weightCol: Param[String]

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    Definition Classes
    HasWeightCol

  92. def write: MLWriter

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    Definition Classes
    StackingClassifier → MLWritable

Inherited from MLWritable

Inherited from StackingClassifierParams

Inherited from ClassifierParams

Inherited from HasRawPredictionCol

Inherited from StackingParams

Inherited from HasBaseLearners

Inherited from HasStacker

Inherited from HasWeightCol

Inherited from HasParallelism

Inherited from Predictor[Vector, StackingClassifier, StackingClassificationModel]

Inherited from PredictorParams

Inherited from HasPredictionCol

Inherited from HasFeaturesCol

Inherited from HasLabelCol

Inherited from Estimator[StackingClassificationModel]

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

Ungrouped