Class/Object

org.apache.spark.ml.classification

StackingClassificationModel

Related Docs: object StackingClassificationModel | package classification

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class StackingClassificationModel extends PredictionModel[Vector, StackingClassificationModel] with StackingClassifierParams with MLWritable

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

Instance Constructors

  1. new StackingClassificationModel(models: Array[EnsemblePredictionModelType], stack: EnsemblePredictionModelType)

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  2. new StackingClassificationModel(uid: String, models: Array[EnsemblePredictionModelType], stack: EnsemblePredictionModelType)

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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[_]): StackingClassificationModel.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): StackingClassificationModel

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    Definition Classes
    StackingClassificationModel → Model → Transformer → 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. final def extractParamMap(): ParamMap

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    Definition Classes
    Params

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

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    Definition Classes
    Params

  18. final val featuresCol: Param[String]

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    Definition Classes
    HasFeaturesCol

  19. def featuresDataType: DataType

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    Attributes
    protected
    Definition Classes
    PredictionModel

  20. def finalize(): Unit

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

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

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    Definition Classes
    HasBaseLearners

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

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    Definition Classes
    Params

  23. def getBaseLearners: Array[EnsemblePredictorType]

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    Definition Classes
    HasBaseLearners

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

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    Definition Classes
    AnyRef → Any

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

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    Definition Classes
    Params

  26. final def getFeaturesCol: String

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    Definition Classes
    HasFeaturesCol

  27. final def getLabelCol: String

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    Definition Classes
    HasLabelCol

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

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    Definition Classes
    Params

  29. def getParallelism: Int

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    Definition Classes
    HasParallelism

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

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    Definition Classes
    Params

  31. final def getPredictionCol: String

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    Definition Classes
    HasPredictionCol

  32. final def getRawPredictionCol: String

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    Definition Classes
    HasRawPredictionCol

  33. def getStacker: EnsemblePredictorType

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    Definition Classes
    HasStacker

  34. final def getWeightCol: String

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    Definition Classes
    HasWeightCol

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

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    Definition Classes
    Params

  36. def hasParam(paramName: String): Boolean

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    Definition Classes
    Params

  37. def hasParent: Boolean

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    Definition Classes
    Model

  38. def hashCode(): Int

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    Definition Classes
    AnyRef → Any

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

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    Attributes
    protected
    Definition Classes
    Logging

  40. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Definition Classes
    Params

  42. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

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

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    Definition Classes
    Params

  44. def isTraceEnabled(): Boolean

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    Attributes
    protected
    Definition Classes
    Logging

  45. final val labelCol: Param[String]

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    Definition Classes
    HasLabelCol

  46. def log: Logger

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

  53. def logName: String

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

  58. val models: Array[EnsemblePredictionModelType]

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

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    Definition Classes
    AnyRef

  60. final def notify(): Unit

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    Definition Classes
    AnyRef

  61. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  62. def numFeatures: Int

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    Definition Classes
    PredictionModel
    Annotations
    @Since( "1.6.0" )

  63. val parallelism: IntParam

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    Definition Classes
    HasParallelism

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

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    Definition Classes
    Params

  65. var parent: Estimator[StackingClassificationModel]

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    Definition Classes
    Model

  66. def predict(features: Vector): Double

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    Definition Classes
    StackingClassificationModel → PredictionModel

  67. final val predictionCol: Param[String]

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    Definition Classes
    HasPredictionCol

  68. final val rawPredictionCol: Param[String]

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    Definition Classes
    HasRawPredictionCol

  69. def save(path: String): Unit

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

  70. final def set(paramPair: ParamPair[_]): StackingClassificationModel.this.type

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    Attributes
    protected
    Definition Classes
    Params

  71. final def set(param: String, value: Any): StackingClassificationModel.this.type

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    Attributes
    protected
    Definition Classes
    Params

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

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    Definition Classes
    Params

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

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    Attributes
    protected
    Definition Classes
    Params

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

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    Attributes
    protected
    Definition Classes
    Params

  75. def setFeaturesCol(value: String): StackingClassificationModel

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    Definition Classes
    PredictionModel

  76. def setParent(parent: Estimator[StackingClassificationModel]): StackingClassificationModel

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    Definition Classes
    Model

  77. def setPredictionCol(value: String): StackingClassificationModel

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    Definition Classes
    PredictionModel

  78. val stack: EnsemblePredictionModelType

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  79. 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

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

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    Definition Classes
    AnyRef

  81. def toString(): String

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    Definition Classes
    Identifiable → AnyRef → Any

  82. def transform(dataset: Dataset[_]): DataFrame

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    Definition Classes
    PredictionModel → Transformer

  83. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame

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    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )

  84. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame

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

  85. def transformImpl(dataset: Dataset[_]): DataFrame

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    Attributes
    protected
    Definition Classes
    PredictionModel

  86. def transformSchema(schema: StructType): StructType

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    Definition Classes
    PredictionModel → PipelineStage

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

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    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()

  88. val uid: String

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    Definition Classes
    StackingClassificationModel → Identifiable

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

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    Attributes
    protected
    Definition Classes
    ClassifierParams → PredictorParams

  90. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  93. final val weightCol: Param[String]

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    Definition Classes
    HasWeightCol

  94. def write: MLWriter

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    Definition Classes
    StackingClassificationModel → 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 PredictionModel[Vector, StackingClassificationModel]

Inherited from PredictorParams

Inherited from HasPredictionCol

Inherited from HasFeaturesCol

Inherited from HasLabelCol

Inherited from Model[StackingClassificationModel]

Inherited from Transformer

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

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