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

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

Instance Constructors

  1. new StackingClassificationModel(models: Array[EnsemblePredictionModelType], stack: EnsemblePredictionModelType)
  2. new StackingClassificationModel(uid: String, models: Array[EnsemblePredictionModelType], stack: 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[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[_]): StackingClassificationModel.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): StackingClassificationModel
    Definition Classes
    StackingClassificationModel → Model → Transformer → 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. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  21. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  22. final val featuresCol: Param[String]
    Definition Classes
    HasFeaturesCol
  23. def featuresDataType: DataType
    Attributes
    protected
    Definition Classes
    PredictionModel
  24. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.Throwable])
  25. def fitBaseLearner(baseLearner: EnsemblePredictorType, labelColName: String, featuresColName: String, predictionColName: String, weightColName: Option[String])(df: DataFrame): EnsemblePredictionModelType
    Attributes
    protected
    Definition Classes
    HasBaseLearner
  26. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  27. def getBaseLearner: EnsemblePredictorType

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

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

    Definition Classes
    StackingClassifierParams
  39. def getStacker: EnsemblePredictorType

    Definition Classes
    HasStacker
  40. final def getWeightCol: String
    Definition Classes
    HasWeightCol
  41. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  42. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  43. def hasParent: Boolean
    Definition Classes
    Model
  44. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  45. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  46. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  47. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  48. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  49. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  50. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  51. final val labelCol: Param[String]
    Definition Classes
    HasLabelCol
  52. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  53. def logDebug(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  54. def logDebug(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  55. def logError(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  56. def logError(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  57. def logInfo(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  58. def logInfo(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  59. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  60. def logTrace(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  61. def logTrace(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  62. def logWarning(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  63. def logWarning(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  64. val models: Array[EnsemblePredictionModelType]
  65. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  66. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  67. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  68. def numFeatures: Int
    Definition Classes
    PredictionModel
    Annotations
    @Since("1.6.0")
  69. val parallelism: IntParam
    Definition Classes
    HasParallelism
  70. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  71. var parent: Estimator[StackingClassificationModel]
    Definition Classes
    Model
  72. def predict(features: Vector): Double
    Definition Classes
    StackingClassificationModel → PredictionModel
  73. final val predictionCol: Param[String]
    Definition Classes
    HasPredictionCol
  74. final val rawPredictionCol: Param[String]
    Definition Classes
    HasRawPredictionCol
  75. 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.")
  76. final def set(paramPair: ParamPair[_]): StackingClassificationModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  77. final def set(param: String, value: Any): StackingClassificationModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  78. final def set[T](param: Param[T], value: T): StackingClassificationModel.this.type
    Definition Classes
    Params
  79. final def setDefault(paramPairs: ParamPair[_]*): StackingClassificationModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  80. final def setDefault[T](param: Param[T], value: T): StackingClassificationModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  81. def setFeaturesCol(value: String): StackingClassificationModel
    Definition Classes
    PredictionModel
  82. def setParent(parent: Estimator[StackingClassificationModel]): StackingClassificationModel
    Definition Classes
    Model
  83. def setPredictionCol(value: String): StackingClassificationModel
    Definition Classes
    PredictionModel
  84. val stack: EnsemblePredictionModelType
  85. 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
  86. 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
  87. final def synchronized[T0](arg0: => T0): T0
    Definition Classes
    AnyRef
  88. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  89. def transform(dataset: Dataset[_]): DataFrame
    Definition Classes
    PredictionModel → Transformer
  90. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since("2.0.0")
  91. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since("2.0.0") @varargs()
  92. def transformImpl(dataset: Dataset[_]): DataFrame
    Attributes
    protected
    Definition Classes
    PredictionModel
  93. def transformSchema(schema: StructType): StructType
    Definition Classes
    PredictionModel → PipelineStage
  94. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  95. val uid: String
    Definition Classes
    StackingClassificationModel → Identifiable
  96. def validateAndTransformSchema(schema: StructType, fitting: Boolean, featuresDataType: DataType): StructType
    Attributes
    protected
    Definition Classes
    ClassifierParams → PredictorParams
  97. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  98. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  99. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException]) @native()
  100. final val weightCol: Param[String]
    Definition Classes
    HasWeightCol
  101. def write: MLWriter
    Definition Classes
    StackingClassificationModel → 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 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 Identifiable

Inherited from AnyRef

Inherited from Any

getParam

param

Ungrouped