Packages

class TrainedClassifierModel extends AutoTrainedModel[TrainedClassifierModel] with Wrappable with BasicLogging

Model produced by TrainClassifier.

Linear Supertypes
BasicLogging, Wrappable, RWrappable, PythonWrappable, BaseWrappable, AutoTrainedModel[TrainedClassifierModel], HasFeaturesCol, HasLabelCol, ComplexParamsWritable, MLWritable, Model[TrainedClassifierModel], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. TrainedClassifierModel
  2. BasicLogging
  3. Wrappable
  4. RWrappable
  5. PythonWrappable
  6. BaseWrappable
  7. AutoTrainedModel
  8. HasFeaturesCol
  9. HasLabelCol
  10. ComplexParamsWritable
  11. MLWritable
  12. Model
  13. Transformer
  14. PipelineStage
  15. Logging
  16. Params
  17. Serializable
  18. Serializable
  19. Identifiable
  20. AnyRef
  21. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new TrainedClassifierModel()
  2. new TrainedClassifierModel(uid: String)

Value Members

  1. final def clear(param: Param[_]): TrainedClassifierModel.this.type
    Definition Classes
    Params
  2. def copy(extra: ParamMap): TrainedClassifierModel
    Definition Classes
    TrainedClassifierModel → Model → Transformer → PipelineStage → Params
  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. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  9. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  10. def getFeaturesCol: String

    Definition Classes
    HasFeaturesCol
  11. def getLabelCol: String

    Definition Classes
    HasLabelCol
  12. def getLastStage: Transformer

    Retrieve the underlying model.

    Retrieve the underlying model.

    returns

    The underlying model.

    Definition Classes
    AutoTrainedModel
  13. def getLevels: Array[Any]
  14. def getModel: PipelineModel
    Definition Classes
    AutoTrainedModel
  15. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  16. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  17. def getParamMap: ParamMap

    Retrieve the param map from the underlying model.

    Retrieve the param map from the underlying model.

    returns

    The param map from the underlying model.

    Definition Classes
    AutoTrainedModel
  18. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  19. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  20. def hasParent: Boolean
    Definition Classes
    Model
  21. def hasScoreColumns(model: Transformer): Boolean
  22. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  23. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  24. val labelCol: Param[String]

    The name of the label column

    The name of the label column

    Definition Classes
    HasLabelCol
  25. val levels: UntypedArrayParam
  26. def logClass(): Unit
    Definition Classes
    BasicLogging
  27. def logFit[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  28. def logPredict[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  29. def logTrain[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  30. def logTransform[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  31. def logVerb[T](verb: String, f: ⇒ T): T
    Definition Classes
    BasicLogging
  32. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  33. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  34. val model: TransformerParam
    Definition Classes
    AutoTrainedModel
  35. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  36. var parent: Estimator[TrainedClassifierModel]
    Definition Classes
    Model
  37. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  38. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  39. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  40. final def set[T](param: Param[T], value: T): TrainedClassifierModel.this.type
    Definition Classes
    Params
  41. def setFeaturesCol(value: String): TrainedClassifierModel.this.type

    Definition Classes
    HasFeaturesCol
  42. def setLabelCol(value: String): TrainedClassifierModel.this.type

    Definition Classes
    HasLabelCol
  43. def setLevels(v: Array[Any]): TrainedClassifierModel.this.type
  44. def setModel(v: PipelineModel): TrainedClassifierModel.this.type
    Definition Classes
    AutoTrainedModel
  45. def setParent(parent: Estimator[TrainedClassifierModel]): TrainedClassifierModel
    Definition Classes
    Model
  46. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  47. def transform(dataset: Dataset[_]): DataFrame
    Definition Classes
    TrainedClassifierModel → Transformer
  48. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  49. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  50. def transformSchema(schema: StructType): StructType
    Definition Classes
    TrainedClassifierModel → PipelineStage
    Annotations
    @DeveloperApi()
  51. val uid: String
    Definition Classes
    TrainedClassifierModel → BasicLogging → Identifiable
  52. val ver: String
    Definition Classes
    BasicLogging
  53. def write: MLWriter
    Definition Classes
    ComplexParamsWritable → MLWritable