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

Source
StackingClassifier.scala
Linear Supertypes
MLWritable, StackingClassifierParams, ClassifierParams, HasRawPredictionCol, StackingParams[EnsemblePredictorType], HasBaseLearners[EnsemblePredictorType], HasStacker[EnsemblePredictorType], HasBaseLearner[EnsemblePredictorType], HasWeightCol, HasParallelism, Predictor[Vector, StackingClassifier, StackingClassificationModel], PredictorParams, HasPredictionCol, HasFeaturesCol, HasLabelCol, Estimator[StackingClassificationModel], PipelineStage, Logging, Params, 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. HasBaseLearner
  10. HasWeightCol
  11. HasParallelism
  12. Predictor
  13. PredictorParams
  14. HasPredictionCol
  15. HasFeaturesCol
  16. HasLabelCol
  17. Estimator
  18. PipelineStage
  19. Logging
  20. Params
  21. Serializable
  22. Identifiable
  23. AnyRef
  24. Any
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Visibility
  1. Public
  2. Protected

Instance Constructors

  1. new StackingClassifier()
  2. new StackingClassifier(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[EnsemblePredictorType]

    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. val baseLearners: Param[Array[EnsemblePredictorType]]

    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
  8. final def clear(param: Param[_]): StackingClassifier.this.type
    Definition Classes
    Params
  9. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.CloneNotSupportedException]) @native()
  10. def copy(extra: ParamMap): StackingClassifier
    Definition Classes
    StackingClassifier → Predictor → Estimator → PipelineStage → Params
  11. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  12. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  13. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  14. def equals(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef → Any
  15. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  16. def explainParams(): String
    Definition Classes
    Params
  17. def extractInstances(dataset: Dataset[_], numClasses: Int): RDD[Instance]
    Attributes
    protected
    Definition Classes
    ClassifierParams
  18. def extractInstances(dataset: Dataset[_], validateInstance: (Instance) => Unit): RDD[Instance]
    Attributes
    protected
    Definition Classes
    PredictorParams
  19. def extractInstances(dataset: Dataset[_]): RDD[Instance]
    Attributes
    protected
    Definition Classes
    PredictorParams
  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[_]): StackingClassificationModel
    Definition Classes
    Predictor → Estimator
  26. def fit(dataset: Dataset[_], paramMaps: Seq[ParamMap]): Seq[StackingClassificationModel]
    Definition Classes
    Estimator
    Annotations
    @Since("2.0.0")
  27. def fit(dataset: Dataset[_], paramMap: ParamMap): StackingClassificationModel
    Definition Classes
    Estimator
    Annotations
    @Since("2.0.0")
  28. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): StackingClassificationModel
    Definition Classes
    Estimator
    Annotations
    @Since("2.0.0") @varargs()
  29. def fitBaseLearner(baseLearner: EnsemblePredictorType, 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: EnsemblePredictorType

    Definition Classes
    HasBaseLearner
  32. def getBaseLearners: Array[EnsemblePredictorType]

    Definition Classes
    HasBaseLearners
  33. final def getClass(): Class[_ <: AnyRef]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  34. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  35. final def getFeaturesCol: String
    Definition Classes
    HasFeaturesCol
  36. final def getLabelCol: String
    Definition Classes
    HasLabelCol
  37. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  38. def getParallelism: Int
    Definition Classes
    HasParallelism
  39. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  40. final def getPredictionCol: String
    Definition Classes
    HasPredictionCol
  41. final def getRawPredictionCol: String
    Definition Classes
    HasRawPredictionCol
  42. def getStackMethod: String

    Definition Classes
    StackingClassifierParams
  43. def getStacker: EnsemblePredictorType

    Definition Classes
    HasStacker
  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 hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  48. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  49. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  50. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  51. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  52. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  53. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  54. final val labelCol: Param[String]
    Definition Classes
    HasLabelCol
  55. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  56. def logDebug(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  57. def logDebug(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  58. def logError(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  59. def logError(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  60. def logInfo(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  61. def logInfo(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  62. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  63. def logTrace(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  64. def logTrace(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  65. def logWarning(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  66. def logWarning(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  67. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  68. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  69. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  70. val parallelism: IntParam
    Definition Classes
    HasParallelism
  71. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  72. final val predictionCol: Param[String]
    Definition Classes
    HasPredictionCol
  73. final val rawPredictionCol: Param[String]
    Definition Classes
    HasRawPredictionCol
  74. 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.")
  75. final def set(paramPair: ParamPair[_]): StackingClassifier.this.type
    Attributes
    protected
    Definition Classes
    Params
  76. final def set(param: String, value: Any): StackingClassifier.this.type
    Attributes
    protected
    Definition Classes
    Params
  77. final def set[T](param: Param[T], value: T): StackingClassifier.this.type
    Definition Classes
    Params
  78. def setBaseLearners(value: Array[EnsemblePredictorType]): StackingClassifier.this.type
  79. final def setDefault(paramPairs: ParamPair[_]*): StackingClassifier.this.type
    Attributes
    protected
    Definition Classes
    Params
  80. final def setDefault[T](param: Param[T], value: T): StackingClassifier.this.type
    Attributes
    protected
    Definition Classes
    Params
  81. def setFeaturesCol(value: String): StackingClassifier
    Definition Classes
    Predictor
  82. def setLabelCol(value: String): StackingClassifier
    Definition Classes
    Predictor
  83. def setParallelism(value: Int): StackingClassifier.this.type
  84. def setPredictionCol(value: String): StackingClassifier
    Definition Classes
    Predictor
  85. def setStackMethod(value: String): StackingClassifier.this.type
  86. def setStacker(value: EnsemblePredictorType): StackingClassifier.this.type
  87. val stackMethod: Param[String]

    Discrete (SAMME) or Real (SAMME.R) boosting algorithm.

    Discrete (SAMME) or Real (SAMME.R) boosting algorithm. (case-insensitive) Supported: "class", "raw", "proba". (default = class)

    Definition Classes
    StackingClassifierParams
  88. val stacker: Param[EnsemblePredictorType]

    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
  89. final def synchronized[T0](arg0: => T0): T0
    Definition Classes
    AnyRef
  90. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  91. def train(dataset: Dataset[_]): StackingClassificationModel
    Attributes
    protected
    Definition Classes
    StackingClassifier → Predictor
  92. def transformSchema(schema: StructType): StructType
    Definition Classes
    Predictor → PipelineStage
  93. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  94. val uid: String
    Definition Classes
    StackingClassifier → Identifiable
  95. def validateAndTransformSchema(schema: StructType, fitting: Boolean, featuresDataType: DataType): StructType
    Attributes
    protected
    Definition Classes
    ClassifierParams → PredictorParams
  96. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  97. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  98. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException]) @native()
  99. final val weightCol: Param[String]
    Definition Classes
    HasWeightCol
  100. def write: MLWriter
    Definition Classes
    StackingClassifier → MLWritable

Inherited from MLWritable

Inherited from StackingClassifierParams

Inherited from ClassifierParams

Inherited from HasRawPredictionCol

Inherited from StackingParams[EnsemblePredictorType]

Inherited from HasBaseLearners[EnsemblePredictorType]

Inherited from HasStacker[EnsemblePredictorType]

Inherited from HasBaseLearner[EnsemblePredictorType]

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 Identifiable

Inherited from AnyRef

Inherited from Any

getParam

param

Ungrouped