Packages

trait AutoTrainer[TrainedModel <: Model[TrainedModel]] extends Estimator[TrainedModel] with HasLabelCol with HasInputCols with ComplexParamsWritable with HasFeaturesCol with Wrappable

Defines common inheritance and parameters across trainers.

Linear Supertypes
Wrappable, DotnetWrappable, RWrappable, PythonWrappable, BaseWrappable, HasFeaturesCol, ComplexParamsWritable, MLWritable, HasInputCols, HasLabelCol, Estimator[TrainedModel], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
Known Subclasses
TrainClassifier, TrainRegressor
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. AutoTrainer
  2. Wrappable
  3. DotnetWrappable
  4. RWrappable
  5. PythonWrappable
  6. BaseWrappable
  7. HasFeaturesCol
  8. ComplexParamsWritable
  9. MLWritable
  10. HasInputCols
  11. HasLabelCol
  12. Estimator
  13. PipelineStage
  14. Logging
  15. Params
  16. Serializable
  17. Serializable
  18. Identifiable
  19. AnyRef
  20. Any
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Visibility
  1. Public
  2. All

Abstract Value Members

  1. abstract def copy(extra: ParamMap): Estimator[TrainedModel]
    Definition Classes
    Estimator → PipelineStage → Params
  2. abstract def fit(dataset: Dataset[_]): TrainedModel
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  3. abstract def modelDoc: String

    Doc for model to run.

  4. abstract def transformSchema(schema: StructType): StructType
    Definition Classes
    PipelineStage
  5. abstract val uid: String
    Definition Classes
    Identifiable

Concrete Value Members

  1. final def clear(param: Param[_]): AutoTrainer.this.type
    Definition Classes
    Params
  2. def dotnetAdditionalMethods: String
    Definition Classes
    DotnetWrappable
  3. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  4. def explainParams(): String
    Definition Classes
    Params
  5. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  6. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  7. val featuresCol: Param[String]

    The name of the features column

    The name of the features column

    Definition Classes
    HasFeaturesCol
  8. def fit(dataset: Dataset[_], paramMaps: Seq[ParamMap]): Seq[TrainedModel]
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  9. def fit(dataset: Dataset[_], paramMap: ParamMap): TrainedModel
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  10. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): TrainedModel
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()
  11. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  12. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  13. def getFeaturesCol: String

    Definition Classes
    HasFeaturesCol
  14. def getInputCols: Array[String]

    Definition Classes
    HasInputCols
  15. def getLabelCol: String

    Definition Classes
    HasLabelCol
  16. def getModel: Estimator[_ <: Model[_]]

  17. def getNumFeatures: Int

  18. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  19. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  20. def getParamInfo(p: Param[_]): ParamInfo[_]
    Definition Classes
    BaseWrappable
  21. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  22. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  23. val inputCols: StringArrayParam

    The names of the inputColumns

    The names of the inputColumns

    Definition Classes
    HasInputCols
  24. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  25. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  26. val labelCol: Param[String]

    The name of the label column

    The name of the label column

    Definition Classes
    HasLabelCol
  27. def makeDotnetFile(conf: CodegenConfig): Unit
    Definition Classes
    DotnetWrappable
  28. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  29. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  30. val model: EstimatorParam

    Model to run.

    Model to run. See doc on derived classes.

  31. val numFeatures: IntParam

    Number of features to hash to

  32. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  33. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  34. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  35. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  36. final def set[T](param: Param[T], value: T): AutoTrainer.this.type
    Definition Classes
    Params
  37. def setFeaturesCol(value: String): AutoTrainer.this.type

    Definition Classes
    HasFeaturesCol
  38. def setInputCols(value: Array[String]): AutoTrainer.this.type

    Definition Classes
    HasInputCols
  39. def setLabelCol(value: String): AutoTrainer.this.type

    Definition Classes
    HasLabelCol
  40. def setModel(value: Estimator[_ <: Model[_]]): AutoTrainer.this.type

  41. def setNumFeatures(value: Int): AutoTrainer.this.type

  42. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  43. def write: MLWriter
    Definition Classes
    ComplexParamsWritable → MLWritable